Climate Resilient Crop Zoning in Tamil Nadu, India: A 25 year assessment of major food crops

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Understanding the spatial performance of major food crops is essential for sustaining productivity in heterogeneous agro‑ecological regions. This study examines the spatio‑temporal dynamics of Efficient Cropping Zones (ECZ) for eight major food crops—rice, maize, sorghum, pearl millet, finger millet, red gram, green gram, and black gram—across Tamil Nadu over a 25‑year period (2000–2025). District‑level area and yield data were used to compute the Relative Yield Index (RYI) and Relative Spread Index (RSI), classifying districts into Most Efficient (MECZ), Yield Efficient (YECZ), Area Efficient (AECZ), and Non‑Efficient Cropping Zones (NECZ). Results reveal pronounced shifts in cropping efficiency driven by rainfall variability, monsoon fluctuations, groundwater depletion, soil fertility decline, and changing farmer preferences. Rice remained largely yield‑efficient in delta districts, while western and southern interior districts transitioned toward NECZ due to altered rainfall distribution and water stress. Maize showed expanding MECZ/YECZ zones supported by hybrid adoption and irrigation access, whereas sorghum and cumbu exhibited widespread efficiency decline linked to erratic monsoon performance. Millets retained resilience in traditional dryland belts, while pulses displayed contrasting trends, with black gram showing notable improvement and red/green gram exhibiting rainfall‑sensitive fluctuations. NECZ hotspots across multiple crops highlight priority districts for climate‑smart diversification toward drought‑tolerant millets, pulses, and oilseeds. Overall, the study demonstrates the value of periodic ECZ‑based assessments as a climate‑informed decision‑support tool for optimizing resource allocation, guiding crop diversification, and strengthening climate‑resilient food systems in Tamil Nadu. Efficient Cropping zones rainfall variability food crops productivity Spatio-temporal analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction 1.1 Background Cereal based farming system dominated by rice, wheat, maize, sorghum, cumbu (pearl millet) and ragi (finger millet) form the backbone of food security and rural livelihoods across Indian states. Pulses complement these systems by enhancing nutritional security and soil fertility through sequential cropping, intercropping, and rice-fallow cultivation. However, sustaining productivity in these systems has become increasingly challenging due to rapid climatic shifts, groundwater depletion, and land-use shifts. Tamil Nadu, located in the semi-arid southern peninsular India, exhibits strong spatial and temporal variability in crop performance, largely driven by fluctuations in southwest and northeast monsoon rainfall, rising temperatures, and resource constraints (Murugan & Madhumitha 2024 ). Understanding how climate variability influences crop distribution and performance is therefore essential for climate-resilient agricultural planning. The Efficient Cropping Zone (ECZ) framework provides a diagnostic approach to evaluate spatial patterns of crop efficiency using both yield and area performance indicators. By identifying districts with high or low efficiency, ECZ analysis supports targeted interventions, crop diversification, and resource optimization under changing climatic conditions. ( Divyadharshini et al., 2025 ). This long-term, climate-informed zoning approach is particularly relevant for Tamil Nadu, where monsoon-dependent agriculture is highly sensitive to rainfall variability and emerging climatic stressors. 1.2 Efficient Cropping Zone (ECZ) approaches The Efficient Cropping Zone (ECZ) framework has emerged as a valuable tool for assessing spatial variations in crop performance by integrating both productivity and area indicators. Early applications in Tamil Nadu were pioneered by Kokilavani and Geethalakshmi ( 2013 ), who delineated efficient zones for rice, maize, and groundnut, demonstrating the utility of ECZ analysis for regional agricultural planning. Subsequent studies expanded the framework to a wider range of crops including Bengal gram, cotton, potato, chillies, banana, mango, turmeric, and coriander (Pradipa et al., 2018 ; Khatua et al., 2020 ; Kowshika et al., 2020 ) highlighting its adaptability across diverse crop types and agro‑ecological settings. These studies consistently revealed that ECZ classifications are dynamic, reflecting the combined influence of climatic variability, technological adoption, market forces, and resource availability. Recent advancements have strengthened the analytical capacity of ECZ assessments through the integration of geospatial tools and multi‑criteria decision-making approaches. Rajkumar ( 2020 ) and Sathiyamurthi et al. ( 2024 ) employed GIS and Analytical Hierarchy Process (AHP) techniques to refine agro‑climatic zonation and crop suitability mapping in Tamil Nadu, incorporating datasets on rainfall, temperature, soil characteristics, and groundwater availability. Similarly, Shunmugapriya et al. ( 2021 ) demonstrated that combining Multi‑Criteria Decision Analysis (MCDA) with GIS enhances the spatial precision and decision-support value of crop zoning frameworks. Furthermore, periodic ECZ evaluations are essential for capturing the evolving agricultural landscape shaped by shifts in farmer crop preferences, land‑use changes, and variations in labour availability. These dynamic factors necessitate regular updates to zoning frameworks to ensure their continued relevance and adaptability to emerging climatic and socio‑economic challenges. The present study applies the ECZ framework to major food crops in Tamil Nadu over a 25‑year period (2001–2025), providing a long-term perspective on spatial efficiency shifts and their implications for climate‑resilient agricultural planning. 1.3 Agro climatic factors and cropping efficiency Cropping efficiency in Tamil Nadu is strongly influenced by agro-climatic factors such as monsoon rainfall variability, evapotranspiration rates, soil moisture availability, and irrigation access. Multi-temporal remote sensing studies (Pazhanivelan et al., 2025 ) have shown significant shifts in cropping patterns driven by fluctuations in southwest and northeast monsoon rainfall. Rainfall variability plays a critical role in determining sowing windows, crop establishment, and yield stability, particularly in rainfed regions. Comparative assessments highlight the superior drought tolerance and water-use efficiency of millets and sorghum relative to maize under semi-arid conditions (Negri et al., 2024 ; Harish et al., 2024 ), underscoring their suitability in districts experiencing declining rainfall or frequent dry spells. Incorporating additional agro-climatic variables such as slope, soil depth, groundwater availability, and temperature stress enhances the precision of crop suitability and zoning analyses (Shunmugapriya et al., 2021 ). These factors collectively influence transitions among MECZ, YECZ, AECZ, and NECZ categories, reflecting the sensitivity of crop performance to climatic and resource constraints. Understanding these agro-climatic drivers is essential for interpreting long-term ECZ shifts and for designing climate-resilient cropping strategies across Tamil Nadu. 1.4 Crop diversification and climate resilience Crop diversification is widely recognized as a key strategy for enhancing resilience to climatic extremes and sustaining productivity in vulnerable agro‑ecosystems. Integrating millets and pulses into cereal‑based systems improves soil health, water‑use efficiency, and nutritional security (Jain et al., 2024 ; Mukherjee et al., 2025 ). Millets, in particular, are increasingly promoted as climate‑resilient “future smart foods” due to their tolerance to drought, heat, and poor soils (Saleem et al., 2023 ). The ECZ framework plays an important role in identifying Non‑Efficient Cropping Zone (NECZ) districts and recommending agro‑ecologically suitable alternatives. Persisting with non‑efficient crops in climatically unsuitable regions leads to suboptimal land and water use, reduced productivity, and heightened vulnerability to climate variability. While earlier studies have focused on individual crops or shorter time periods, the present study provides a comprehensive 25‑year ECZ assessment for major food crops across Tamil Nadu. This long‑term evaluation captures persistent NECZ hotspots, identifies climate‑driven shifts in cropping efficiency, and supports evidence‑based diversification strategies for climate‑resilient agricultural planning. 2. Materials and Methods 2.1 Data Sources Data on area, production, and productivity of major food crops (rice, maize, sorghum, cumbu, ragi, red gram, green gram, and black gram) for a 25‑year period (2000–2025) were obtained from the Season and Crop Report published by the Government of Tamil Nadu. The dataset was grouped into three time windows viz., 2000–2005, 2010–2015, and 2020–2025 to assess decadal shifts in cropping efficiency. 2.2 Efficient Cropping Zone (ECZ) Classification District level cropping efficiency was assessed using the Relative Spread Index (RSI) and Relative Yield Index (RYI): $$\:RSI=\:\frac{\begin{array}{c}Area\:of\:the\:crop\:expressed\:as\:percentage\:of\:\\\:total\:cultivable\:area\:in\:the\:district\end{array}}{\begin{array}{c}Area\:of\:the\:crop\:expressed\:as\:percentage\:of\:\\\:total\:cultivable\:area\:in\:the\:state\end{array}}\:\times\:100$$ $$\:RYI=\:\frac{Mean\:yield\:of\:the\:crop\:in\:the\:district}{Mean\:yield\:of\:the\:crop\:in\:the\:state}\:\times\:100$$ RSI RYI Cropping Zone > 100 > 100 Most Efficient Cropping Zone (MECZ) 100 Yield Efficient Cropping Zone (YECZ) > 100 < 100 Area Efficient Cropping Zone (AECZ) < 100 < 100 Non- Efficient Cropping Zone (NECZ) 2.3 Climate Data and Trend Analysis District wise rainfall data for Tamil Nadu for the period 2000–2025 were used to assess long‑term climate variability. Annual and seasonal (SWM and NEM) rainfall trends were computed using linear trend analysis to identify districts experiencing significant increases or declines in monsoon rainfall. Rainfall anomalies were calculated relative to the long‑term mean to capture interannual variability. Rainfall was selected as the primary climate variable due to its dominant influence on crop establishment, soil moisture availability, and yield stability in Tamil Nadu’s monsoon‑dependent agricultural systems. Temperature trends, drought frequency, and groundwater stress reported in published IMD, CGWB, and peer‑reviewed studies were incorporated as contextual indicators to interpret climate‑related shifts in cropping efficiency. These climate signals were used to support the interpretation of transitions among MECZ, YECZ, AECZ, and NECZ categories across the 25‑year period. 2.4 Spatial Analysis District‑wise ECZ classifications for each time period were mapped using GIS to visualize spatial patterns and transitions. Changes in ECZ categories were analysed to identify persistent efficiency zones, emerging NECZ hotspots, and districts showing improvement or decline over time. 3. Results 3.1 Rainfall Trends in Tamil Nadu (2000–2023) Tamil Nadu’s rainfall during 2000–2025 (Fig. 1 ) shows pronounced interannual and seasonal variability, with annual totals ranging from 598 mm (2016) to 1401 mm (2021). The long‑term mean of 970 mm closely matches the IMD normal. The period 2000–2009 recorded an average of 930 mm, followed by 950 mm during 2010–2019, while 2020–2025 exhibited a marked increase with a mean of 1190 mm. Seasonally, the Northeast Monsoon (NEM) remained the dominant contributor, varying widely from 174 mm (2016) to 829 mm (2005). The Southwest Monsoon (SWM) contributed a relatively stable 300–400 mm annually, with peaks in 2017 (421 mm) and 2022 (478 mm). Rainfall during the Hot Weather Period (HWP) and Cold Weather Period (CWP) remained low, except for isolated spikes such as 2020 (CWP: 155 mm) and 2025 (HWP: 229 mm). The inter‑decadal periods showed contrasting patterns: 2006–2010 experienced moderate to above‑normal rainfall in 2007, 2008, and 2010, whereas 2016–2020 was marked by the severe drought of 2016 followed by strong monsoon recovery in 2019 and 2020. 3.2 Implications of Rainfall Variability for Crop Efficient Zones (CEZ) Rainfall variability across the 26-year period played a decisive role in shaping CEZ transitions for major crops in Tamil Nadu. The inter-decadal climate anomalies (2006–2010 and 2016–2020) acted as critical transition phases influencing the decadal ECZ outcomes. The drought year 2016, with the lowest annual rainfall (598 mm) and a severely deficient NEM (174 mm), likely contributed to the expansion of Non-Efficient Cropping Zones (NECZ) for rice and pulses, particularly in eastern and southern districts. Conversely, the strong monsoon years of 2007, 2010, 2019, and 2020 would have supported recovery in cropping efficiency, enabling districts to regain Yield Efficient (YECZ) or Most Efficient (MECZ) status in the subsequent decadal window. Years with exceptionally high NEM rainfall, such as 2005 and 2021, created favorable moisture conditions that enhanced the performance of rice, black gram, and maize, contributing to MECZ expansion in deltaic and western agro-climatic zones. The sustained increase in rainfall during 2020–2025 likely improved CEZ status for millets and pulses in traditionally dryland belts, reflecting enhanced resilience under improved monsoon conditions. Overall, the CEZ transitions observed across the three decadal periods (2000–05, 2010–15, 2020–25) can be directly linked to the intervening rainfall fluctuations, underscoring the sensitivity of cropping efficiency to both long-term and short-term climate variability. 3.3 Crop wise district level ECZ The Efficient Cropping Zone analysis revealed the spatial and temporal shifts in the performance of major food crops across between 2000 and 2025. The distribution of MECZ, YECZ, AECZ, and NECZ categories varied considerably across decades, reflecting the combined influence of changing rainfall patterns, soil fertility dynamics, irrigation access, and management intensity. Several districts transitioned into Non‑Efficient Cropping Zones (NECZ), underscoring the growing vulnerability of crop production systems and the need for adaptive, climate‑responsive strategies. The decadal ECZ patterns provide a diagnostic basis for identifying suitable alternative crops for non‑efficient regions and for designing region‑specific interventions to enhance cropping efficiency. 3.4 Rice The ECZ classification for rice from 2000 to 2025 (Fig. 2 ) illustrates a distinct spatial reorganization of efficiency zones, with traditional rice-growing regions retaining relative stability while interior districts exhibited increasing vulnerability. During the initial phase (2000–2005), rice crop across Tamil Nadu showed an equal distribution patter, with 12 districts (≈ 33%) under MECZ, 12 (≈ 33%) under YECZ, 8 (≈ 22%) under AECZ, and 5 (≈ 14%) under NECZ. In the second phase (2010–2015), there had been improvement in yield efficiency, with YECZ bolstering to 16 districts (≈ 44%), especially with districts such as Perambalur, Ariyalur, Dharmapuri, Krishnagiri, and Madurai. Simultaneously, AECZ districts increased to 10, sustaining stable rice area efficiency in traditional command areas like Thanjavur, Thiruvarur, Nagapattinam, Pudukkottai, and Ramanathapuram, supported by consistent Cauvery and groundwater-fed irrigation. In contrast, MECZ districts suffered a downfall to 10 districts, demonstrating that mid-level performance regions were either improving toward yield efficiency or regressing due to climate variability. In 2020–2025, the efficiency pattern shows indicates additional polarization, with YECZ dominating 18 districts (≈ 50%), highlighting yield-centred developments, while AECZ remained consistent with 10 districts (≈ 28%), and MECZ dropped to just 5 (≈ 14%). NECZ districts surged again to 4 (≈ 11%), primarily in interior regions like Virudhunagar, Coimbatore, Karur, and Thoothukudi, showing climate-induced stress and decreased water availability. Deltaic zones such as Thanjavur, Thiruvarur, Nagapattinam, and Pudukkottai maintained their consistency under AECZ classification, ensuring the strength of canal irrigation and traditional paddy ecosystems. Positive YECZ transitions were demonstrated by districts like Kancheepuram, Villupuram, and Madurai which reflected adaptive management and technology infusion. On the other hand, the regression to NECZ in Coimbatore and Karur demonstrates the detrimental effects of temperature rise, unpredictable rainfall and groundwater depletion on rice sustainability. Districts that experienced sharp NEM deficits during 2016 and uneven SWM recovery showed the strongest regression toward NECZ, underscoring rice’s sensitivity to monsoon variability. Overall, the ECZ patterns for rice reveal a consistent stability in delta and coastal districts, where supported by canal irrigation, groundwater access, and favourable soils, while southern and western interior districts show declining efficiency and increasing NECZ prevalence. These trends emphasize the need for targeted interventions, including climate‑resilient varieties, improved water‑use efficiency, and zone‑specific nutrient and crop management strategies to sustain rice productivity under evolving climatic and resource constraints. 3.5 Maize The Efficient Cropping Zone of Maize crop in Tamil Nadu between 2000 and 2025 (Fig. 3 ) highlights a strong production efficiency of the, exhibiting both resilience in traditional belts and emerging regional disparities across districts. During the initial period (2000–2005), maize demonstrated significant expansion and stability, reinforcing its position as a major commercial crop in Tamil Nadu. MECZ dominated in 15 districts (≈ 42%), followed by YECZ in 9 (≈ 25%), and both AECZ and NECZ accounting for 4 (≈ 11%) and 9 (≈ 25%) districts, respectively. Maize productive zones such as Salem, Erode, Tiruppur, Namakkal, Madurai, Pudukkottai, Thanjavur were benefitted from improved soil fertility and moderate rainfall favouring maize crop. In the second period (2010–2015), maize cultivation exhibited relative stability with signs of diversification. MECZ declined to 14 districts (≈ 39%), while YECZ remained constant at 9 districts (≈ 25%), AECZ held 4 districts (≈ 11%), and NECZ slightly increased to 10 (≈ 28%). Yield efficiency was maintained in major maize belts such as Namakkal, Krishnagiri, and Pudukkottai. New AECZ emergence observed in Ariyalur and Cuddalore districts indicated area stability, whereas Kancheepuram, Thiruvarur and Nagapattinam districts shifted to NECZ reflected the constraints in deltaic and northern districts. By 2020–2025, a clear efficiency shift from area to yield was observed. MECZ districts reduced to 9 (≈ 25%), while YECZ expanded to 12 districts (≈ 33%) indicating improved productivity in several regions. AECZ observed in 7 districts (≈ 19%), particularly in Madurai, Thoothukudi, and Tenkasi, where maize continues to be cultivated as a stable dryland crop. NECZ persisted in 9 districts (≈ 25%) with Kancheepuram, Coimbatore, and Theni remaining non-efficient due to crop diversification, rainfall variability, and groundwater depletion. The decline of traditional maize districts such as Coimbatore and Thiruvarur into NECZ is a notable concern. Yield‑efficient districts corresponded with years of favourable SWM rainfall (2007, 2010, 2017), while NECZ expansion in Coimbatore and Theni aligned with declining post‑2015 rainfall and groundwater stress. Over the 25 years trend in maize ECZ reveals a distinct west–east and north–south gradient. Western and southern districts consistently exhibiting MECZ/YECZ status, attributed to technological advancements, irrigation, and hybrid utilization, while northern and deltaic districts fluctuated between AECZ and NECZ, due to erratic rainfall, soil moisture limitation and competing crop preferences. Sustaining maize productivity in Tamil Nadu require a climate-resilient intensification approach that emphasizes precision nutrient and water management, stress-tolerant hybrids, soil conservation, and integrated cropping systems to stabilize yields and enhance profitability in vulnerable NECZ regions. 3.6 Sorghum The spatial and temporal ECZ for Sorghum from 2000 to 2025 (Fig. 4 ) reflects its strong adaptation to rainfed and semi-arid ecosystems, systems, while also revealing a progressive decline in efficiency across several districts. During the initial period (2000–2005), sorghum performed nearly half of the state, with 17 districts ≈ 47% under MECZ, 7 districts (≈ 19%) under YECZ, 4 districts (≈ 11%) under AECZ, and 9 districts (≈ 25%) under NECZ. High‑performing districts such as Namakkal, Dindigul, Madurai, and Tiruppur reflected the crop’s suitability to dryland conditions, while NECZ pockets in Cuddalore, Thiruvannamalai, and Pudukkottai indicated localized constraints. In the second period (2010–2015), sorghum experienced a marked decline in efficiency. NECZ expanded to 13 districts (≈ 36%), while MECZ reduced to 11 districts (≈ 31%). This shift was most evident in the north-eastern and delta districts, where erratic rainfall, declining soil fertility, and competing crop choices reduced sorghum performance. Only 7 districts (≈ 19%) including Tirunelveli, Nagapattinam, and Kanyakumari were YECZ highlighting localized yield improvements. AECZ expanded to 6 districts (≈ 17%), especially in Salem, Namakkal and Tiruppur districts possibly due to enhanced area efficiency through improved cropping intensity and fodder-oriented sorghum cultivation. The most recent period of 2020–2025 shows widespread vulnerability, with half the state fall under NECZ (18 districts ≈ 50%). MECZ contracted to 6 districts (≈ 17%), mainly in Dindigul, Namakkal, Tiruchirapalli, and Tenkasi, districts where adaptive agronomy and supplementary irrigation sustained moderate efficiency. AECZ increased sharply to 11 districts (≈ 31%), signifying a shift toward area stability rather than productivity gains. Only Nagapattinam and Dharmapuri districts (≈ 6%) remained in YECZ, demonstrating isolated yield persistence despite broad climatic deterioration. The widespread NECZ expansion after 2015 coincided with repeated SWM shortfalls and the 2016 drought, which disproportionately affected sorghum-based dryland belts. Overall, the analysis shows a southern and western concentration, with a pronounced decline in north-eastern districts. The expansion of NECZ underscores the need for climate-smart technologies like drought resistant varieties, improved soil moisture conservation and precision agriculture to sustain sorghum cultivation in dryland ecosystems. 3.7 Cumbu (Pearl millet) The ECZ analysis for Cumbu from 2000 to 2025 (Fig. 5 ) reveals a relatively greater spatial stability compared to other cereals, although notable transitions occurred across decades. In the initial years (2000–2005), cumbu exhibited strong performance with YECZ in 13 districts (≈ 36%) and MECZ in 11 districts (≈ 31%), AECZ in 6 districts (≈ 17%) and NECZ in 7 districts (≈ 19%). District such as Dharmapuri and Krishnagiri, Dindigul, Chengalpattu and Tenkasi districts demonstrated high yield efficiency, linked to adaptive crop management and local seed diversity. During 2010–2015, both MECZ (13 districts; ≈36%) and NECZ (11 districts; ≈31%) expanded, while YECZ declined to 9 district (≈ 25%) and AECZ dropped to 4 districts (≈ 11%). Declining cultivation area and changing land-use priorities were evident in districts such as Kancheepuram, Coimbatore, Namakkal, and Tiruchirappalli, contributing to NECZ. Dharmapuri, Krishnagiri and Pudukkottai districts maintained YECZ status, reflecting consistent yield performance. By 2020–2025, NECZ expanded to 14 districts (≈ 39%), indicating reduced area and productivity in several interior districts. MECZ declined to 10 districts (≈ 28%), while YECZ remained stable in 9 districts (≈ 25%) and AECS persisted in 4 districts (≈ 11%). District such as Madurai, Theni, Kanyakumari, Dharmapuri and Krishnagiri continued to sustain yield efficiency, whereas Coimbatore, Eorde, Tiruppur and Ramanathapuram showed widespread NECZ due to land-use change, crop preference shifts or climatic stress. Despite its drought tolerance, NECZ expansion after 2016 reflected the cumulative impact of erratic SWM rainfall and reduced early-season moisture essential for cumbu establishment. Across 25-year period, cumbu shows an gradual shift from YECZ toward both MECZ and NECZ, reflecting a variable performance across regions. Delta districts like Thanjavur, Nagapattinam and Mayiladuthurai remain less suitable for cumbu, whereas southern and north-western dry tracts continue to support the crop under resource constraints. Strengthening cumbu cultivation will require drought‑tolerant varieties, soil nutrient management, rainwater harvesting, and millet‑based intercropping systems to enhance resilience. 3.8 Ragi (Finger millet) The ECZ analysis for ragi from 2000 to 2025 (Fig. 6 ) indicates a balanced yet shifting pattern, reflecting the crop’s adaptability to semi‑arid environments and its sensitivity to land‑use and climatic changes. During 2000–2005, ragi exhibited strong performance with 11 districts (≈ 31%) under MECZ and 12 districts (≈ 33%) under YECZ. AECZ accounted for 3 districts (≈ 8%) and NECZ observed in 11 districts (≈ 31%). High performing districts included Kallakurichi, Ranipet and Tenkasi districts, while Dharmapuri and Krishnagiri maintained yield efficiency. Districts such as Namakkal, Coimbatore, Perambalur and Pudukkottai showed low performance. During 2010–2015, MECZ expanded to 13 districts (≈ 36%), particularly in Kallakurichi, Erode, and Thiruvarur. YECZ covered 11 districts (≈ 31%), including Vellore, Thanjavur, and Theni. AECZ remained minimal (≈ 6%), restricted to Dharmapuri and Krishnagiri, NECZ persisted in 11 districts (≈ 31%), notably in Namakkal, Coimbatore, and Pudukkottai indicating continued challenges. By 2020–2025, ragi showed a clear shift toward yield efficiency, with YECZ expanding to 15 districts (≈ 42%) owing to Vellore, Dindigul, Virudhunagar, Tirunelveli, and Kanyakumari, where integrated millet promotion programs and improved varieties endorsed yield performance. MECZ declined sharply to 4 districts (≈ 11%), while ACEZ increased to 5 districts (≈ 14%), particularly in Dharmapuri, Krishnagiri, and Salem. NECZ spread to 13 districts, including Coimbatore, Namakkal, Perambalur, and Theni, reflecting ongoing challenges. Yield-efficient districts corresponded with improved monsoon performance during 2019–2020, while NECZ pockets in interior districts reflected prolonged dry spells during 2012–2016. Overall, ragi shows a westward and southward stabilization over the 25 years, with a decline in North-eastern and delta regions. District such as Kallakurichi, Tenkasi, Dindigul and Tirunelveli districts consistently maintained MECZ and YECZ status, underscoring their suitability for millet based system. Strengthening ragi cultivation will require climate‑resilient varieties, improved soil moisture management, and value‑addition initiatives to enhance both productivity and livelihood resilience. 3.9 Black gram The ECZ classification for Black gram from 2000 to 2025 (Fig. 7 ) shows a clear progressive improvement in cropping efficiency, with several districts transitioning from NECZ to YECZ over time. During the initial period (2000–2005), black gram showed high vulnerability with NECZ dominating in 15 districts (≈ 42%). MECZ covered 11 districts (≈ 31%), while YECZ and AECZ accounted for 6 (≈ 17%) and 5 districts (≈ 14%), respectively. High-performing MECZ districts included Chengalpattu, Kallakurichi, Ranipet, Tirupatur, Salem, Nilgris, Tiruppur, Tenkasi, Ariyalur, Mayiladuthurai and Tanjavur districts. Interior districts like Namakkal, Dindigul, Madurai, Virudhunagar, Villupuram and Dharmapuri were yield efficient, while coastal districts were area efficient due to rice – pulse cropping system. In the second period (2010–2015) blackgram exhibited significant recovery under YECZ expanding into 15 districts (≈ 42%), while MECZ scaling up to 10 districts (≈ 28%). Positively the NECZ declined sharply to 8 districts (≈ 22%) indicating improved productivity and area stability. District such as Erode, Krishnagiri, Tiruchirappalli, and Pudukkottai districts shifted from NECZ to YECZ, reflecting the impact of pulse-based cropping intensification and improved varieties. AECZ persisted in the Thiruvarur, Thanjavur, Nagapattinam and Thoothukudi districts, where the rice fallow pulse cropping system is traditionally followed. By 2020–2025, YECZ spread expanded to 16 districts (≈ 44%), including districts like Namakkal, Dharmapuri, Madurai, and Kanyakumari. MECZ remained stable (9 districts. ≈25%), persisting in Chengalpattu, Ranipet, Tirupatthur, and The Nilgiris. AECZ persisted in 5 districts (≈ 14%), while NECZ declined to 7 districts (≈ 19%), mainly in Ramanathapuram, Karur, Dindigul, and Theni, where moisture constrained productivity. The shift from NECZ to YECZ in many districts aligned with favourable NEM rainfall during 2010, 2019, and 2020, which supported rice-fallow pulse productivity. Overall, black gram shows a strong shift from area‑based to yield‑based efficiency, with sustained performance in north‑eastern, western, and southern districts. Strengthening climate‑smart pulse technologies, short‑duration varieties, and rice‑fallow intensification can further enhance black gram productivity and smallholder resilience. 3.10 Green gram The ECZ classification of green gram crop in Tamil Nadu over the period of 25 years (2000–2025) exhibits a dynamic shift toward yield dominance (Fig. 8 ) although several districts continue to face climatic and resource-related constraints. During 2000–2005, greengram saw a balance between MECZ and YECZ with equal distribution in 13 districts (≈ 36%) each. AECZ observed in 6 districts (≈ 17%) and NECZ in 5 districts (≈ 14%). Strong MECZ performance was noted in Chengalpattu, Tiruvallur, Ranipet, Kallakurichi, Namakkal, Tiruppur, The Nilgiris, Ariyalur, Mayiladuthurai, Virudhunagar, Tenkasi and Salem, while central and northwestern districts were highly yield efficient. The NECZ pockets were concentrated in northern districts along with Coimbatore and Cuddalore. In the second period (2010–2015), green gram crop’s MECZ declined to 9 districts (≈ 25%), while YECZ slightly decreased to 11 (≈ 31%), and NECZ expanded sharply to 13 (≈ 36%), reflecting climatic instability and reduced area under pulses in favour of cash crops. AECZ remained in 4 districts, including Nagapattinam and Thoothukudi, where rice-pulse and rainfed pulse systems support area stability. Namakkal and Virudhunagar shifted from MECZ to AECZ, indicating simultaneous area expansion and yield reduction. In 2020–2025, green gram ECZ showed a partial recovery with YECZ expanding to 15 districts (≈ 42%), mainly in Northern and Western Zone districts like Dharmapuri, Krishnagiri, Erode, Perambalur, and Namakkal. ACEZ has also risen to 8 districts (≈ 22%), marking their territorial stability in Nagapattinam, Thiruvarur, and Mayiladuthurai, where rice-pulse cropping system is followed. There was a further decrease in MECZ to 4 districts (≈ 11%), while NECZ slightly increased to 10 districts (≈ 28%), notably in Kancheepuram, Villupuram, and Ramanathapuram, where soil degradation and erratic monsoons become the primary barriers. Green gram efficiency improved in districts receiving above-normal NEM rainfall (2005, 2021), while NECZ persisted in regions affected by repeated early-season moisture deficits. Overall, green gram efficiency demonstrates sensitivity to rainfall variability and land-use shifts. Strengthening short-duration varieties, moisture-conserving agronomy, and rice-fallow intensification will be critical for improving green gram performance in NECZ regions. 3.11 Red gram The ECZ classification for red gram from 2000 to 2025 (Fig. 9 ) reflects the crop’s strong adaptation to dryland ecosystems, while also highlighting increasing vulnerability in several interior districts. During 2000–2005, red gram exhibited moderate performance with MECZ in 16 districts (≈ 44%), YECZ in 13 districts (≈ 36%), AECZ in 5 districts (≈ 14%) and NECZ in 3 districts (≈ 8%). Districts such as Dharmapuri, Krishnagiri, and Kallakurichi sustained high productivity due to favourable red soils and moderate rainfall. Yield performance dominated in Thanjavur, Ramanathapuram, and Tirunelveli, while the limited NECZ (3 districts) highlighted the crop’s suitability to dryland farming. Between 2010–2015, MECZ declined to 13 districts (≈ 36%), while YECZ remained steady at 13 (≈ 36%), and NECZ expanded sharply to 9 districts (≈ 25%). AECZ dropped to just 2 districts (≈ 6%), limited to Vellore and Madurai. This period showed a mixed scenario with many MECZ shifted to YECZ/AECZ and vice versa. The rapid expansion of NECZ despite pulse-focused development programmes, indicated emerging climatic and resource constraints. In 2020–2025, a partial recovery was observed. YECZ expanded substantially to 18 districts (≈ 50%), becoming the dominant category, while MECZ declined to 8 districts (≈ 22%), while AECZ rose to 6 districts (≈ 17%). Importantly, NECZ contracted to 5 districts (≈ 14%), signifying yield recovery and better resource utilization. Area efficiency was notable in north-western districts and in Karur, Nagapattinam, and Madurai, whereas several central districts continued to show weak performance. The expansion of YECZ during 2020–2025 corresponded with improved monsoon distribution, whereas NECZ districts reflected the prolonged dry spells of 2012–2016. Overall, red gram exhibited a gradual shift toward yield-led efficiency across north-eastern, western, and southern districts over the 25-year period. This improvement may be attributed to enhanced rainfall use efficiency, improved seed technologies, and pulse intensification initiatives. However, deltaic tracts and select interior districts continue to face instability, likely due to land-use changes, competing crop preferences, and rainfall variability. 3.12 Comparative performance of Food crops in Tamil Nadu The performance of the major food crops across Tamil Nadu over the 25 year period is summarised in Table 1 . The observed spatial and temporal shifts across MECZ, YECZ, AECZ, and NECZ categories reflect the combined influence of rainfall variability, technological adoption, market forces, resource availability, and land‑use change. Table 1 Crop performance of major food crops of Tamil Nadu Crop ECZ Trend (2000–2025) Key Zones Major Constraints Overall Performance Rice Gradual decline in area efficiency with stable yield performance Deltaic and semi-delta regions (Cauvery basin) Water scarcity, urban expansion Moderately Efficient Maize Strong upward trend with sustained MECZ dominance Western and central drylands Heat stress, soil nutrient fatigue Highly Efficient Sorghum Declining trend due to area contraction and climatic variability Central dryland tracts Crop substitution, rainfall irregularity Moderately Low Cumbu (Pearl Millet) Stable MECZ and YECZ persistence across dry belts Northern and southern arid belts Urbanization, weak market linkages Highly Stable Ragi (Finger Millet) Cyclical efficiency pattern with notable yield recovery Western uplands and southern hill slopes Climate variability, shrinking cultivation area Resilient and Adaptive Black Gram (Urd Bean) Continuous improvement with expanding efficient zones Western and northern agro-climatic regions Pest pressure, rainfall fluctuation Highly Promising Green Gram (Mung Bean) Variable efficiency with yield gains in irrigated zones North-eastern and western transitional belts Terminal drought, low soil moisture Moderately Stable Red Gram (Pigeon Pea) Moderate yield efficiency gains and stable MECZ continuity North-central and western dry tracts Moisture stress, erratic rainfall Moderately Efficient Rice, the state’s primary staple, showed a gradual shift from MECZ/YECZ to AECZ/NECZ in several interior districts during the recent decade, largely due to water scarcity, stagnated productivity, unseasonal rainfall, floods during seedling or harvest stages, and urban expansion. Frequent NEM deficits (especially 2012–2016) and erratic SWM onset further weakened rice efficiency in non‑delta districts. In contrast, maize has strengthened its position, transitioning from YECZ to sustained MECZ dominance, particularly in western districts such as Namakkal, Salem, and Dindigul. Maize efficiency closely aligned with favourable SWM years (2007, 2010, 2017), while irrigated belts buffered the impacts of dry spells. Sorghum exhibited a marked decline, with many earlier YECZ and AECZ belts shifting into NECZ, especially in northern and central drylands, mainly due to the dominance of maize. The prolonged dry spells during 2012–2016 and reduced early‑season moisture critically affected sorghum establishment. Cumbu remained relatively stable, with persistent MECZ/YECZ zones in Dharmapuri, Krishnagiri, and Tenkasi. However, erratic SWM distribution after 2015 caused NECZ expansion in interior belts despite cumbu’s drought tolerance. Ragi expanded until 2010–2020 but showed mild regression thereafter, though western uplands and southern slopes continued to support strong performance. Yield gains corresponded with improved monsoon years (2019–2020), while NECZ pockets reflected repeated dry spells in the preceding decade. Among pulses, black gram showed the most notable improvement, with several NECZ districts transitioning into YECZ/MECZ. High NEM rainfall years (2010, 2019, 2020) supported rice‑fallow pulse productivity. Green gram displayed variable efficiency, with gains in irrigated belts but persistent NECZ pockets in moisture‑limited regions. Its sensitivity to early‑season rainfall deficits explains the instability in interior districts. Red gram maintained moderate efficiency, with stable MECZ continuity in north‑central and western dry tracts. Improved rainfall distribution during 2020–2025 supported YECZ expansion, while earlier drought years constrained central districts. Overall, the comparative assessment highlights the need to recognise emerging vulnerabilities and shifting crop suitability. These insights are essential for designing climate‑smart interventions and region‑specific diversification strategies to sustain productivity under evolving agro‑climatic conditions. 3.13 Crop Diversification recommendations for NECZ in for different crops NECZ districts represent areas where existing crop choices are no longer sustainable due to rainfall variability, groundwater depletion, soil moisture stress, and declining productivity. Diversification toward short‑duration, drought‑tolerant, and resource‑efficient crops is essential to enhance resilience and optimize land use. Crops consistently performing well in MECZ and YECZ, such as cumbu, ragi, black gram, and green gram, offer suitable alternatives for NECZ districts, especially where water‑intensive crops like rice and maize show declining efficiency. Similarly, NECZ regions for sorghum and cumbu may benefit from pulses or oilseeds that align better with local agro‑climatic conditions. Table 2 provides district‑wise diversification options based on ECZ outcomes, highlighting suitable alternative crops and the rationale for each recommendation. These targeted interventions support climate‑smart planning and help stabilize productivity in vulnerable regions. Table 2 Recommendations for NECZ in Tamil Nadu Crop Districts under NECZ (2020–2025) Suggested Alternative Crops Agro Climatic and Soil related Justification Rice Coimbatore, Karur Virudhunagar, Thoothukudi Millets (Cumbu, Ragi), Pulses (Cowpea, Green gram), Groundnut, Sesame Red and sandy loam soils with limited irrigation; low to moderate rainfall (< 800 mm); suited for dryland diversification and short-duration crops. Maize Kancheepuram, Tiruvannamalai, Coimbatore, Karur, Thiruvarur, Theni, Ramanathapuram, Sivagangai, Tirunelveli Pulses (Black gram, Green gram), Oilseeds (Groundnut, Sesame), Sorghum, Cotton Semi-arid tracts with red soils and erratic rainfall; suitable for short-duration, drought-tolerant crops and mixed farming systems. Sorghum Tiruvallur, Cuddalore, Villupuram, Vellore Tiruvannamalai, Krishnagiri, Coimbatore, Erode, Perambalur, Ariyalur, Pudukkottai, Thanjavur, Thiruvarur, Madurai, Ramanathapuram, Sivagangai, Tirunelveli, The Nilgiris Finger Millet, Maize, Sunflower, Groundnut, Cotton, Vegetables (hill zones) Adaptable to red loam and black soils; suitable for 600–1000 mm rainfall and temperature-tolerant systems; promotes income diversification. Cumbu (Pearl Millet) Kancheepuram, Namakkal, Coimbatore, Tiruppur, Erode, Tiruchirappalli, Karur, Perambalur, Pudukkottai, Thanjavur, Dindigul, Ramanathapuram, Sivagangai, Tirunelveli Pulses (Black gram, Cowpea), Oilseeds (Groundnut, Sesame, Castor), Maize, Cotton Performs better in dry, sandy loam to clay loam soils with low rainfall; ensures higher yield stability and economic resilience in dryland conditions. Ragi (Finger Millet) Kancheepuram, Cuddalore, Villupuram, Tiruvannamalai, Namakkal, Coimbatore, Perambalur, Ariyalur, Pudukkottai, Thiruvarur, Madurai, Theni, The Nilgiris Maize, Sorghum, Groundnut, Pulses, Vegetables (hill zones), Sunflower Red loam and lateritic soils with 600–900 mm rainfall; suited for short-season or high-value crops under rainfed and semi-arid ecosystems. Black Gram (Urd Bean) Tiruppur, Karur, Nagapattinam, Theni, Dindigul, Ramanathapuram, Virudhunagar Green gram, Cowpea, Groundnut, Sesame Thrives in sandy loam to clay loam soils with moderate moisture; suitable as a rotation crop in rainfed tracts; enhances system resilience. Green Gram (Mung Bean) Kancheepuram, Villupuram, Tiruppur, Tiruchirappalli, Karur, Thanjavur, Madurai, Ramanathapuram, Virudhunagar, Tirunelveli Short-duration Pulses (Black gram, Cowpea), Millets, Oilseeds Performs well in sandy loam soils with residual moisture; ideal for post-rainy season cropping under limited irrigation and rainfed systems. Red Gram (Pigeon Pea) Tiruchirappalli, Perambalur, Pudukkottai, Thiruvarur, Dindigul Millets (Cumbu, Ragi), Green gram, Groundnut, Sunflower Suitable for intercropping in red loam and gravelly soils; better moisture utilization in 600–800 mm rainfall zones; enhances soil fertility. 3.14 Climate linked interpretation The long-term ECZ assessment clearly demonstrates that cropping efficiency in Tamil Nadu is strongly shaped by rainfall variability, monsoon behaviour, and resource constraints. Districts that experienced stable or improving monsoon rainfall particularly during the inter-decadal recovery years (2007–2008, 2010, 2019–2020) showed positive transitions toward YECZ and MECZ across rice, maize, black gram, and ragi. In contrast, districts affected by severe rainfall deficits, such as during the 2016 drought, consistently shifted toward NECZ, especially for water-intensive crops like rice and for climate-sensitive pulses such as red gram and green gram. The persistence of NECZ in several interior and western districts highlights the need for climate responsive diversification strategies. Millets (cumbu, ragi) and pulses (black gram, green gram) demonstrated greater resilience in dryland belts, aligning with earlier findings on their superior drought tolerance and water-use efficiency (Negri et al., 2024 ; Harish et al., 2024 ). The ECZ framework thus provides a practical decision support tool for identifying districts where crop substitution, varietal improvement, or resource-conserving agronomy is essential. The results also underscore the importance of integrating agro-climatic indicators rainfall variability, groundwater status, and soil moisture regimes into district-level planning. As highlighted in earlier studies (Pazhanivelan et al., 2025 ; Shunmugapriya et al., 2021 ), climate-informed zoning enables targeted interventions such as drought-tolerant cultivars, micro-irrigation, and soil health restoration. The ECZ transitions observed in this study reinforce the need for periodic updates to cropping recommendations, ensuring that agricultural planning remains aligned with evolving climatic realities and farmer resource conditions. 4. Discussion The synthesis of rainfall trends (2000–2025) with ECZ transitions reveals strong climate sensitivity across Tamil Nadu’s major food crops. The state experienced pronounced interannual variability, with annual rainfall ranging from 598 mm (2016) to 1401 mm (2021), and a marked increase in rainfall during 2020–2025. These fluctuations were mirrored in the spatial dynamics of cropping efficiency. 4.1 Influence of rainfall variability on ECZ transitions Districts receiving consistent or above normal rainfall during key years such as 2007, 2008, 2010, 2019, and 2020 showed improvements in YECZ and MECZ classifications for rice, maize, black gram, and ragi. Conversely, the severe drought of 2016, characterized by the lowest annual rainfall and a highly deficient Northeast Monsoon, corresponded with widespread NECZ expansion across rice, sorghum, cumbu, and pulses. These patterns reinforce the dominant role of monsoon rainfall in determining crop establishment, yield stability, and area persistence, consistent with earlier findings (Murugan & Madhumitha 2024 ; Pazhanivelan et al., 2025 ). 4.2 Crop-specific climate sensitivities Rice and maize exhibited strong dependence on irrigation and monsoon stability. Deltaic districts with canal irrigation maintained AECZ or YECZ status across decades, while interior districts with declining groundwater shifted toward NECZ. Sorghum and cumbu, despite being dryland crops, showed declining efficiency in northern and deltaic districts due to erratic rainfall and land-use shifts, echoing earlier observations on climate-induced millet vulnerability (Negri et al., 2024 ). Pulses displayed contrasting trends, black gram showed notable improvement, transitioning from NECZ to YECZ in many districts, while red gram and green gram remained highly sensitive to rainfall variability and soil moisture stress. These findings align with previous studies emphasizing the need for moisture-conserving agronomy and short-duration varieties in pulse systems (Jain et al., 2024 ; Mukherjee et al., 2025 ). 4.3 Spatial patterns and agro-ecological gradients A consistent west–east and north–south gradient was observed across crops. Western and southern districts benefiting from better groundwater availability, hybrid adoption, and diversified cropping systems maintained MECZ/YECZ status for maize, ragi, and black gram. In contrast, northern and delta districts showed fluctuating efficiency due to rainfall variability, soil constraints, and competing crop choices. These spatial patterns corroborate earlier agro-climatic zonation studies (Rajkumar, 2020 ; Sathiyamurthi et al., 2024 ). 4.4 Implications for climate-resilient planning The integration of rainfall trends with ECZ outcomes highlights the need for climate-resilient cropping strategies tailored to district-specific vulnerabilities. NECZ hotspots identified across cereals and pulses represent priority regions for diversification toward drought-tolerant millets, pulses, and oilseeds. Strengthening micro-irrigation, soil moisture conservation, and climate-resilient varieties will be essential to stabilize yields under increasing rainfall variability. Overall, the ECZ framework, when combined with long-term climate analysis, provides a robust foundation for climate-smart agricultural planning, enabling policymakers and extension systems to align crop recommendations with evolving agro-climatic realities. 5. Policy Recommendations The ECZ assessment highlights clear spatial differences in crop performance across Tamil Nadu, underscoring the need for climate-responsive, zone-specific interventions. 5.1 Strengthen infrastructure in MECZ districts Enhance irrigation reliability, canal maintenance, and groundwater recharge to sustain high productivity. Invest in post-harvest infrastructures to reduce losses and stabilize farmer income. Promote precision nutrient and water management to maintain long-term soil health. 5.2 Expand extension support in YECZ districts Prioritize technology dissemination, including improved varieties, SRI/SSI methods, and integrated nutrient management. Strengthen farmer training and advisory services to expand cultivated area and stabilize yields. Encourage crop insurance uptake to buffer against rainfall variability. 5.3 Target technological interventions in AECZ districts Introduce high-yielding, short-duration, and stress-tolerant cultivars to improve productivity. Promote micro-irrigation, mulching, and soil moisture conservation practices. Support balanced fertilization and soil health restoration in nutrient-depleted regions. 5.4 Diversify cropping systems in NECZ districts Promote millets (cumbu, ragi) and pulses (black gram, green gram, red gram) as climate-resilient alternatives to water-intensive crops. Encourage intercropping and crop rotation to improve soil fertility and reduce climate risk. Integrate rainwater harvesting, farm ponds, and watershed interventions to enhance moisture availability. 5.5 Integrate climate information into district planning Use seasonal rainfall forecasts, drought indices, and ECZ maps to guide sowing decisions and crop advisories. Institutionalize periodic ECZ assessments to update cropping recommendations in line with evolving climatic trends. Strengthen data-driven decision support systems for agriculture departments and extension networks. 6. Conclusion This study provides a comprehensive 25 year assessment of Efficient Cropping Zones (ECZ) for major food crops in Tamil Nadu, integrating spatial crop performance with long-term rainfall variability. The results reveal clear shifts in cropping efficiency driven by monsoon fluctuations, groundwater stress, land-use change, and technological adoption. Deltaic districts maintained stable rice efficiency, while western drylands emerged as strong maize and millet belts. In contrast, several interior districts transitioned into NECZ, particularly during drought-affected years such as 2016. Millets and pulses demonstrated notable resilience, reinforcing their suitability for climate-stressed dryland ecosystems. The ECZ framework proved effective in identifying vulnerability hotspots and guiding diversification strategies. Linking ECZ outcomes with rainfall trends underscores the importance of climate-informed planning, targeted interventions, and adaptive crop choices. Overall, the study highlights the need for periodic ECZ monitoring, district-specific diversification, and climate-smart agronomy to sustain agricultural productivity under increasing climatic uncertainty. The insights generated here provide a robust foundation for policy formulation, extension planning, and long-term climate-resilient agricultural development in Tamil Nadu. Declarations Competing Interests The authors have no relevant financial or non-financial interests to disclose. Funding This work was supported by Foreign Agency funded project of ICAR–CRIDA and CIMMYT–BISA, project titled “Atlas of Climate Adaptation for South Asia (ACASA)” and Department of Science and Technology, Government of India (GOI) through the project entitled “DST-NMSKCC-CEST Sponsored Centre of Excellence on Climate and Disaster Resilience Agriculture (DST/CCP/NMSKCC/CoE/237/2024). The first author Dheebakaran Ga is an Investigator in both the scheme. Author Contribution The authors *Dheebakaran Ga and Raveendran M contributed to the study conception and design. Material preparation, data collection and analysis were performed by* all the authors *. The first draft of the manuscript was written by Dheebakaran Ga and all authors provided comment and corrections on previous versions of the manuscript. All authors read and approved the final manuscript.* Acknowledgement This work was supported by Foreign Agency funded project of ICAR–CRIDA and CIMMYT–BISA, project titled “Atlas of Climate Adaptation for South Asia (ACASA)” and Department of Science and Technology, Government of India (GOI) through the project entitled “DST-NMSKCC-CEST Sponsored Centre of Excellence on Climate and Disaster Resilience Agriculture (DST/CCP/NMSKCC/CoE/237/2024). The first author Dheebakaran Ga is an Investigator in both the scheme. Data Availability The datasets generated and/or analysed during the present study are not publicly accessible due to project‑level restrictions and portions of the dataset were sourced from the Tamil Nadu Government’s Seasonal Crop Report, which is restricted for open public use. However, they may be obtained from the corresponding author upon reasonable request. References Annual Report 2018–2019. 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Supplementary Files floatimage10.png A graphical abstract representing climate resilience in food production through ECZ Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 09 Mar, 2026 Reviewers agreed at journal 09 Feb, 2026 Reviewers agreed at journal 04 Feb, 2026 Reviewers invited by journal 04 Feb, 2026 Editor assigned by journal 29 Jan, 2026 Submission checks completed at journal 29 Jan, 2026 First submitted to journal 28 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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University","correspondingAuthor":false,"prefix":"","firstName":"Senbagavalli","middleName":"","lastName":"Govindasamy","suffix":""},{"id":586057386,"identity":"d1c7aa15-60a0-4d63-a4ea-2be2df353ee1","order_by":8,"name":"Panchulakshmi Marnadu","email":"","orcid":"","institution":"Tamil Nadu Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Panchulakshmi","middleName":"","lastName":"Marnadu","suffix":""}],"badges":[],"createdAt":"2026-01-28 05:23:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8716571/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8716571/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102205581,"identity":"de28a072-b2a2-44c6-94f9-0284d72ad6b5","added_by":"auto","created_at":"2026-02-09 11:43:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":224056,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTemporal variation in annual and seasonal rainfall over Tamil Nadu (2000-25)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8716571/v1/63eb7f75a487db6a7ef8ef65.png"},{"id":102205592,"identity":"5497a35d-794d-4a53-8403-3313ea52f750","added_by":"auto","created_at":"2026-02-09 11:43:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":404330,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDecadal shift in district-wise ECZ for rice in Tamil Nadu.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8716571/v1/0dc19a52f382812a7e19623b.png"},{"id":102205578,"identity":"03f0e18b-8ba6-4dfa-92cd-93e1957370ef","added_by":"auto","created_at":"2026-02-09 11:43:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":415838,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDecadal shift in district wise ECZ for maize in Tamil Nadu.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8716571/v1/8aa75a988147b764275686dc.png"},{"id":102205590,"identity":"257ef4f6-1d41-441f-b192-d545e13321cd","added_by":"auto","created_at":"2026-02-09 11:43:07","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":423743,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDecadal shift in district wise efficient crop zone for sorghum in Tamil Nadu.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8716571/v1/bcc41d65f98a06eaf2b5bffb.png"},{"id":102205582,"identity":"4f4355e8-4688-48d4-8943-5c77aba41f04","added_by":"auto","created_at":"2026-02-09 11:43:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":412900,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDecadal shift in district level ECZ for cumbu in Tamil Nadu.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8716571/v1/3b38d0c1e513970f0295568a.png"},{"id":102205587,"identity":"19f6a203-ca7f-4d73-aff1-52c573a4fb9f","added_by":"auto","created_at":"2026-02-09 11:43:06","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":418436,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDecadal shift in district level ECZ for ragi in Tamil Nadu.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8716571/v1/f2f88101307f566c431bdf0a.png"},{"id":102205589,"identity":"a2033aca-a9e3-41f3-88ac-d469ae5c1bd9","added_by":"auto","created_at":"2026-02-09 11:43:07","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":449547,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDecadal shift in district wise efficient crop zone for black gram in Tamil Nadu.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8716571/v1/c5a069e2f3f5e3aa5b7a10bc.png"},{"id":102205593,"identity":"ccc84bd4-9e35-46d2-94c4-883850274429","added_by":"auto","created_at":"2026-02-09 11:43:09","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":448094,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDecadal shift in district level ECZ for green gram in Tamil Nadu.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8716571/v1/9dc0772bf01d4022f6951b4b.png"},{"id":102205588,"identity":"384aa2b4-0b2e-4a68-a51a-52b703603663","added_by":"auto","created_at":"2026-02-09 11:43:07","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":426213,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDecadal shift in district level ECZ for red gram in Tamil Nadu.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-8716571/v1/f31113d85d5fafbd2eac8650.png"},{"id":102205690,"identity":"9f40e58d-0bbb-4376-9c6e-5e8d2fdfe285","added_by":"auto","created_at":"2026-02-09 11:43:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5224449,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8716571/v1/7babca83-20b4-429a-9baa-e3da7a1d7164.pdf"},{"id":102205577,"identity":"1a3d009f-5d53-467b-b558-7d0a8d5d558f","added_by":"auto","created_at":"2026-02-09 11:43:01","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2407566,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA graphical abstract representing climate resilience in food production through ECZ\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-8716571/v1/295d9332e8dd7ef54de784d8.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Climate Resilient Crop Zoning in Tamil Nadu, India: A 25 year assessment of major food crops","fulltext":[{"header":"1. Introduction","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1 Background\u003c/h2\u003e \u003cp\u003eCereal based farming system dominated by rice, wheat, maize, sorghum, cumbu (pearl millet) and ragi (finger millet) form the backbone of food security and rural livelihoods across Indian states. Pulses complement these systems by enhancing nutritional security and soil fertility through sequential cropping, intercropping, and rice-fallow cultivation. However, sustaining productivity in these systems has become increasingly challenging due to rapid climatic shifts, groundwater depletion, and land-use shifts. Tamil Nadu, located in the semi-arid southern peninsular India, exhibits strong spatial and temporal variability in crop performance, largely driven by fluctuations in southwest and northeast monsoon rainfall, rising temperatures, and resource constraints (Murugan \u0026amp; Madhumitha \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Understanding how climate variability influences crop distribution and performance is therefore essential for climate-resilient agricultural planning. The Efficient Cropping Zone (ECZ) framework provides a diagnostic approach to evaluate spatial patterns of crop efficiency using both yield and area performance indicators. By identifying districts with high or low efficiency, ECZ analysis supports targeted interventions, crop diversification, and resource optimization under changing climatic conditions. \u003cb\u003e(\u003c/b\u003eDivyadharshini et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This long-term, climate-informed zoning approach is particularly relevant for Tamil Nadu, where monsoon-dependent agriculture is highly sensitive to rainfall variability and emerging climatic stressors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.2 Efficient Cropping Zone (ECZ) approaches\u003c/h2\u003e \u003cp\u003eThe Efficient Cropping Zone (ECZ) framework has emerged as a valuable tool for assessing spatial variations in crop performance by integrating both productivity and area indicators. Early applications in Tamil Nadu were pioneered by Kokilavani and Geethalakshmi (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), who delineated efficient zones for rice, maize, and groundnut, demonstrating the utility of ECZ analysis for regional agricultural planning. Subsequent studies expanded the framework to a wider range of crops including Bengal gram, cotton, potato, chillies, banana, mango, turmeric, and coriander (Pradipa et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Khatua et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kowshika et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) highlighting its adaptability across diverse crop types and agro‑ecological settings. These studies consistently revealed that ECZ classifications are dynamic, reflecting the combined influence of climatic variability, technological adoption, market forces, and resource availability.\u003c/p\u003e \u003cp\u003eRecent advancements have strengthened the analytical capacity of ECZ assessments through the integration of geospatial tools and multi‑criteria decision-making approaches. Rajkumar (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and Sathiyamurthi et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) employed GIS and Analytical Hierarchy Process (AHP) techniques to refine agro‑climatic zonation and crop suitability mapping in Tamil Nadu, incorporating datasets on rainfall, temperature, soil characteristics, and groundwater availability. Similarly, Shunmugapriya et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) demonstrated that combining Multi‑Criteria Decision Analysis (MCDA) with GIS enhances the spatial precision and decision-support value of crop zoning frameworks.\u003c/p\u003e \u003cp\u003eFurthermore, periodic ECZ evaluations are essential for capturing the evolving agricultural landscape shaped by shifts in farmer crop preferences, land‑use changes, and variations in labour availability. These dynamic factors necessitate regular updates to zoning frameworks to ensure their continued relevance and adaptability to emerging climatic and socio‑economic challenges. The present study applies the ECZ framework to major food crops in Tamil Nadu over a 25‑year period (2001\u0026ndash;2025), providing a long-term perspective on spatial efficiency shifts and their implications for climate‑resilient agricultural planning.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e1.3 Agro climatic factors and cropping efficiency\u003c/h2\u003e \u003cp\u003eCropping efficiency in Tamil Nadu is strongly influenced by agro-climatic factors such as monsoon rainfall variability, evapotranspiration rates, soil moisture availability, and irrigation access. Multi-temporal remote sensing studies (Pazhanivelan et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) have shown significant shifts in cropping patterns driven by fluctuations in southwest and northeast monsoon rainfall. Rainfall variability plays a critical role in determining sowing windows, crop establishment, and yield stability, particularly in rainfed regions.\u003c/p\u003e \u003cp\u003eComparative assessments highlight the superior drought tolerance and water-use efficiency of millets and sorghum relative to maize under semi-arid conditions (Negri et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Harish et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), underscoring their suitability in districts experiencing declining rainfall or frequent dry spells. Incorporating additional agro-climatic variables such as slope, soil depth, groundwater availability, and temperature stress enhances the precision of crop suitability and zoning analyses (Shunmugapriya et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These factors collectively influence transitions among MECZ, YECZ, AECZ, and NECZ categories, reflecting the sensitivity of crop performance to climatic and resource constraints.\u003c/p\u003e \u003cp\u003eUnderstanding these agro-climatic drivers is essential for interpreting long-term ECZ shifts and for designing climate-resilient cropping strategies across Tamil Nadu.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e1.4 Crop diversification and climate resilience\u003c/h2\u003e \u003cp\u003eCrop diversification is widely recognized as a key strategy for enhancing resilience to climatic extremes and sustaining productivity in vulnerable agro‑ecosystems. Integrating millets and pulses into cereal‑based systems improves soil health, water‑use efficiency, and nutritional security (Jain et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Mukherjee et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Millets, in particular, are increasingly promoted as climate‑resilient \u0026ldquo;future smart foods\u0026rdquo; due to their tolerance to drought, heat, and poor soils (Saleem et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe ECZ framework plays an important role in identifying Non‑Efficient Cropping Zone (NECZ) districts and recommending agro‑ecologically suitable alternatives. Persisting with non‑efficient crops in climatically unsuitable regions leads to suboptimal land and water use, reduced productivity, and heightened vulnerability to climate variability. While earlier studies have focused on individual crops or shorter time periods, the present study provides a comprehensive 25‑year ECZ assessment for major food crops across Tamil Nadu. This long‑term evaluation captures persistent NECZ hotspots, identifies climate‑driven shifts in cropping efficiency, and supports evidence‑based diversification strategies for climate‑resilient agricultural planning.\u003c/p\u003e \u003c/div\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data Sources\u003c/h2\u003e \u003cp\u003eData on area, production, and productivity of major food crops (rice, maize, sorghum, cumbu, ragi, red gram, green gram, and black gram) for a 25‑year period (2000\u0026ndash;2025) were obtained from the Season and Crop Report published by the Government of Tamil Nadu. The dataset was grouped into three time windows viz., 2000\u0026ndash;2005, 2010\u0026ndash;2015, and 2020\u0026ndash;2025 to assess decadal shifts in cropping efficiency.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Efficient Cropping Zone (ECZ) Classification\u003c/h2\u003e \u003cp\u003eDistrict level cropping efficiency was assessed using the Relative Spread Index (RSI) and Relative Yield Index (RYI):\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:RSI=\\:\\frac{\\begin{array}{c}Area\\:of\\:the\\:crop\\:expressed\\:as\\:percentage\\:of\\:\\\\\\:total\\:cultivable\\:area\\:in\\:the\\:district\\end{array}}{\\begin{array}{c}Area\\:of\\:the\\:crop\\:expressed\\:as\\:percentage\\:of\\:\\\\\\:total\\:cultivable\\:area\\:in\\:the\\:state\\end{array}}\\:\\times\\:100$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:RYI=\\:\\frac{Mean\\:yield\\:of\\:the\\:crop\\:in\\:the\\:district}{Mean\\:yield\\:of\\:the\\:crop\\:in\\:the\\:state}\\:\\times\\:100$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRSI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRYI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCropping Zone\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMost Efficient Cropping Zone (MECZ)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYield Efficient Cropping Zone (YECZ)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArea Efficient Cropping Zone (AECZ)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon- Efficient Cropping Zone (NECZ)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Climate Data and Trend Analysis\u003c/h2\u003e \u003cp\u003eDistrict wise rainfall data for Tamil Nadu for the period 2000\u0026ndash;2025 were used to assess long‑term climate variability. Annual and seasonal (SWM and NEM) rainfall trends were computed using linear trend analysis to identify districts experiencing significant increases or declines in monsoon rainfall. Rainfall anomalies were calculated relative to the long‑term mean to capture interannual variability.\u003c/p\u003e \u003cp\u003eRainfall was selected as the primary climate variable due to its dominant influence on crop establishment, soil moisture availability, and yield stability in Tamil Nadu\u0026rsquo;s monsoon‑dependent agricultural systems. Temperature trends, drought frequency, and groundwater stress reported in published IMD, CGWB, and peer‑reviewed studies were incorporated as contextual indicators to interpret climate‑related shifts in cropping efficiency. These climate signals were used to support the interpretation of transitions among MECZ, YECZ, AECZ, and NECZ categories across the 25‑year period.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Spatial Analysis\u003c/h2\u003e \u003cp\u003eDistrict‑wise ECZ classifications for each time period were mapped using GIS to visualize spatial patterns and transitions. Changes in ECZ categories were analysed to identify persistent efficiency zones, emerging NECZ hotspots, and districts showing improvement or decline over time.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Rainfall Trends in Tamil Nadu (2000\u0026ndash;2023)\u003c/h2\u003e \u003cp\u003eTamil Nadu\u0026rsquo;s rainfall during 2000\u0026ndash;2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) shows pronounced interannual and seasonal variability, with annual totals ranging from 598 mm (2016) to 1401 mm (2021). The long‑term mean of 970 mm closely matches the IMD normal. The period 2000\u0026ndash;2009 recorded an average of 930 mm, followed by 950 mm during 2010\u0026ndash;2019, while 2020\u0026ndash;2025 exhibited a marked increase with a mean of 1190 mm.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSeasonally, the Northeast Monsoon (NEM) remained the dominant contributor, varying widely from 174 mm (2016) to 829 mm (2005). The Southwest Monsoon (SWM) contributed a relatively stable 300\u0026ndash;400 mm annually, with peaks in 2017 (421 mm) and 2022 (478 mm). Rainfall during the Hot Weather Period (HWP) and Cold Weather Period (CWP) remained low, except for isolated spikes such as 2020 (CWP: 155 mm) and 2025 (HWP: 229 mm). The inter‑decadal periods showed contrasting patterns: 2006\u0026ndash;2010 experienced moderate to above‑normal rainfall in 2007, 2008, and 2010, whereas 2016\u0026ndash;2020 was marked by the severe drought of 2016 followed by strong monsoon recovery in 2019 and 2020.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Implications of Rainfall Variability for Crop Efficient Zones (CEZ)\u003c/h2\u003e \u003cp\u003eRainfall variability across the 26-year period played a decisive role in shaping CEZ transitions for major crops in Tamil Nadu. The inter-decadal climate anomalies (2006\u0026ndash;2010 and 2016\u0026ndash;2020) acted as critical transition phases influencing the decadal ECZ outcomes.\u003c/p\u003e \u003cp\u003eThe drought year 2016, with the lowest annual rainfall (598 mm) and a severely deficient NEM (174 mm), likely contributed to the expansion of Non-Efficient Cropping Zones (NECZ) for rice and pulses, particularly in eastern and southern districts. Conversely, the strong monsoon years of 2007, 2010, 2019, and 2020 would have supported recovery in cropping efficiency, enabling districts to regain Yield Efficient (YECZ) or Most Efficient (MECZ) status in the subsequent decadal window.\u003c/p\u003e \u003cp\u003eYears with exceptionally high NEM rainfall, such as 2005 and 2021, created favorable moisture conditions that enhanced the performance of rice, black gram, and maize, contributing to MECZ expansion in deltaic and western agro-climatic zones. The sustained increase in rainfall during 2020\u0026ndash;2025 likely improved CEZ status for millets and pulses in traditionally dryland belts, reflecting enhanced resilience under improved monsoon conditions. Overall, the CEZ transitions observed across the three decadal periods (2000\u0026ndash;05, 2010\u0026ndash;15, 2020\u0026ndash;25) can be directly linked to the intervening rainfall fluctuations, underscoring the sensitivity of cropping efficiency to both long-term and short-term climate variability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Crop wise district level ECZ\u003c/h2\u003e \u003cp\u003eThe Efficient Cropping Zone analysis revealed the spatial and temporal shifts in the performance of major food crops across between 2000 and 2025. The distribution of MECZ, YECZ, AECZ, and NECZ categories varied considerably across decades, reflecting the combined influence of changing rainfall patterns, soil fertility dynamics, irrigation access, and management intensity. Several districts transitioned into Non‑Efficient Cropping Zones (NECZ), underscoring the growing vulnerability of crop production systems and the need for adaptive, climate‑responsive strategies. The decadal ECZ patterns provide a diagnostic basis for identifying suitable alternative crops for non‑efficient regions and for designing region‑specific interventions to enhance cropping efficiency.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Rice\u003c/h2\u003e \u003cp\u003eThe ECZ classification for rice from 2000 to 2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) illustrates a distinct spatial reorganization of efficiency zones, with traditional rice-growing regions retaining relative stability while interior districts exhibited increasing vulnerability.\u003c/p\u003e \u003cp\u003eDuring the initial phase (2000\u0026ndash;2005), rice crop across Tamil Nadu showed an equal distribution patter, with 12 districts (\u0026asymp;\u0026thinsp;33%) under MECZ, 12 (\u0026asymp;\u0026thinsp;33%) under YECZ, 8 (\u0026asymp;\u0026thinsp;22%) under AECZ, and 5 (\u0026asymp;\u0026thinsp;14%) under NECZ.\u003c/p\u003e \u003cp\u003eIn the second phase (2010\u0026ndash;2015), there had been improvement in yield efficiency, with YECZ bolstering to 16 districts (\u0026asymp;\u0026thinsp;44%), especially with districts such as Perambalur, Ariyalur, Dharmapuri, Krishnagiri, and Madurai. Simultaneously, AECZ districts increased to 10, sustaining stable rice area efficiency in traditional command areas like Thanjavur, Thiruvarur, Nagapattinam, Pudukkottai, and Ramanathapuram, supported by consistent Cauvery and groundwater-fed irrigation. In contrast, MECZ districts suffered a downfall to 10 districts, demonstrating that mid-level performance regions were either improving toward yield efficiency or regressing due to climate variability.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn 2020\u0026ndash;2025, the efficiency pattern shows indicates additional polarization, with YECZ dominating 18 districts (\u0026asymp;\u0026thinsp;50%), highlighting yield-centred developments, while AECZ remained consistent with 10 districts (\u0026asymp;\u0026thinsp;28%), and MECZ dropped to just 5 (\u0026asymp;\u0026thinsp;14%). NECZ districts surged again to 4 (\u0026asymp;\u0026thinsp;11%), primarily in interior regions like Virudhunagar, Coimbatore, Karur, and Thoothukudi, showing climate-induced stress and decreased water availability. Deltaic zones such as Thanjavur, Thiruvarur, Nagapattinam, and Pudukkottai maintained their consistency under AECZ classification, ensuring the strength of canal irrigation and traditional paddy ecosystems. Positive YECZ transitions were demonstrated by districts like Kancheepuram, Villupuram, and Madurai which reflected adaptive management and technology infusion. On the other hand, the regression to NECZ in Coimbatore and Karur demonstrates the detrimental effects of temperature rise, unpredictable rainfall and groundwater depletion on rice sustainability.\u003c/p\u003e \u003cp\u003eDistricts that experienced sharp NEM deficits during 2016 and uneven SWM recovery showed the strongest regression toward NECZ, underscoring rice\u0026rsquo;s sensitivity to monsoon variability.\u003c/p\u003e \u003cp\u003eOverall, the ECZ patterns for rice reveal a consistent stability in delta and coastal districts, where supported by canal irrigation, groundwater access, and favourable soils, while southern and western interior districts show declining efficiency and increasing NECZ prevalence. These trends emphasize the need for targeted interventions, including climate‑resilient varieties, improved water‑use efficiency, and zone‑specific nutrient and crop management strategies to sustain rice productivity under evolving climatic and resource constraints.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Maize\u003c/h2\u003e \u003cp\u003eThe Efficient Cropping Zone of Maize crop in Tamil Nadu between 2000 and 2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) highlights a strong production efficiency of the, exhibiting both resilience in traditional belts and emerging regional disparities across districts. During the initial period (2000\u0026ndash;2005), maize demonstrated significant expansion and stability, reinforcing its position as a major commercial crop in Tamil Nadu. MECZ dominated in 15 districts (\u0026asymp;\u0026thinsp;42%), followed by YECZ in 9 (\u0026asymp;\u0026thinsp;25%), and both AECZ and NECZ accounting for 4 (\u0026asymp;\u0026thinsp;11%) and 9 (\u0026asymp;\u0026thinsp;25%) districts, respectively. Maize productive zones such as Salem, Erode, Tiruppur, Namakkal, Madurai, Pudukkottai, Thanjavur were benefitted from improved soil fertility and moderate rainfall favouring maize crop.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the second period (2010\u0026ndash;2015), maize cultivation exhibited relative stability with signs of diversification. MECZ declined to 14 districts (\u0026asymp;\u0026thinsp;39%), while YECZ remained constant at 9 districts (\u0026asymp;\u0026thinsp;25%), AECZ held 4 districts (\u0026asymp;\u0026thinsp;11%), and NECZ slightly increased to 10 (\u0026asymp;\u0026thinsp;28%). Yield efficiency was maintained in major maize belts such as Namakkal, Krishnagiri, and Pudukkottai. New AECZ emergence observed in Ariyalur and Cuddalore districts indicated area stability, whereas Kancheepuram, Thiruvarur and Nagapattinam districts shifted to NECZ reflected the constraints in deltaic and northern districts.\u003c/p\u003e \u003cp\u003eBy 2020\u0026ndash;2025, a clear efficiency shift from area to yield was observed. MECZ districts reduced to 9 (\u0026asymp;\u0026thinsp;25%), while YECZ expanded to 12 districts (\u0026asymp;\u0026thinsp;33%) indicating improved productivity in several regions. AECZ observed in 7 districts (\u0026asymp;\u0026thinsp;19%), particularly in Madurai, Thoothukudi, and Tenkasi, where maize continues to be cultivated as a stable dryland crop. NECZ persisted in 9 districts (\u0026asymp;\u0026thinsp;25%) with Kancheepuram, Coimbatore, and Theni remaining non-efficient due to crop diversification, rainfall variability, and groundwater depletion. The decline of traditional maize districts such as Coimbatore and Thiruvarur into NECZ is a notable concern.\u003c/p\u003e \u003cp\u003eYield‑efficient districts corresponded with years of favourable SWM rainfall (2007, 2010, 2017), while NECZ expansion in Coimbatore and Theni aligned with declining post‑2015 rainfall and groundwater stress.\u003c/p\u003e \u003cp\u003eOver the 25 years trend in maize ECZ reveals a distinct west\u0026ndash;east and north\u0026ndash;south gradient. Western and southern districts consistently exhibiting MECZ/YECZ status, attributed to technological advancements, irrigation, and hybrid utilization, while northern and deltaic districts fluctuated between AECZ and NECZ, due to erratic rainfall, soil moisture limitation and competing crop preferences. Sustaining maize productivity in Tamil Nadu require a climate-resilient intensification approach that emphasizes precision nutrient and water management, stress-tolerant hybrids, soil conservation, and integrated cropping systems to stabilize yields and enhance profitability in vulnerable NECZ regions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Sorghum\u003c/h2\u003e \u003cp\u003eThe spatial and temporal ECZ for Sorghum from 2000 to 2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) reflects its strong adaptation to rainfed and semi-arid ecosystems, systems, while also revealing a progressive decline in efficiency across several districts.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDuring the initial period (2000\u0026ndash;2005), sorghum performed nearly half of the state, with 17 districts\u0026thinsp;\u0026asymp;\u0026thinsp;47% under MECZ, 7 districts (\u0026asymp;\u0026thinsp;19%) under YECZ, 4 districts (\u0026asymp;\u0026thinsp;11%) under AECZ, and 9 districts (\u0026asymp;\u0026thinsp;25%) under NECZ. High‑performing districts such as Namakkal, Dindigul, Madurai, and Tiruppur reflected the crop\u0026rsquo;s suitability to dryland conditions, while NECZ pockets in Cuddalore, Thiruvannamalai, and Pudukkottai indicated localized constraints.\u003c/p\u003e \u003cp\u003eIn the second period (2010\u0026ndash;2015), sorghum experienced a marked decline in efficiency. NECZ expanded to 13 districts (\u0026asymp;\u0026thinsp;36%), while MECZ reduced to 11 districts (\u0026asymp;\u0026thinsp;31%). This shift was most evident in the north-eastern and delta districts, where erratic rainfall, declining soil fertility, and competing crop choices reduced sorghum performance. Only 7 districts (\u0026asymp;\u0026thinsp;19%) including Tirunelveli, Nagapattinam, and Kanyakumari were YECZ highlighting localized yield improvements. AECZ expanded to 6 districts (\u0026asymp;\u0026thinsp;17%), especially in Salem, Namakkal and Tiruppur districts possibly due to enhanced area efficiency through improved cropping intensity and fodder-oriented sorghum cultivation.\u003c/p\u003e \u003cp\u003eThe most recent period of 2020\u0026ndash;2025 shows widespread vulnerability, with half the state fall under NECZ (18 districts\u0026thinsp;\u0026asymp;\u0026thinsp;50%). MECZ contracted to 6 districts (\u0026asymp;\u0026thinsp;17%), mainly in Dindigul, Namakkal, Tiruchirapalli, and Tenkasi, districts where adaptive agronomy and supplementary irrigation sustained moderate efficiency. AECZ increased sharply to 11 districts (\u0026asymp;\u0026thinsp;31%), signifying a shift toward area stability rather than productivity gains. Only Nagapattinam and Dharmapuri districts (\u0026asymp;\u0026thinsp;6%) remained in YECZ, demonstrating isolated yield persistence despite broad climatic deterioration.\u003c/p\u003e \u003cp\u003eThe widespread NECZ expansion after 2015 coincided with repeated SWM shortfalls and the 2016 drought, which disproportionately affected sorghum-based dryland belts.\u003c/p\u003e \u003cp\u003eOverall, the analysis shows a southern and western concentration, with a pronounced decline in north-eastern districts. The expansion of NECZ underscores the need for climate-smart technologies like drought resistant varieties, improved soil moisture conservation and precision agriculture to sustain sorghum cultivation in dryland ecosystems.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Cumbu (Pearl millet)\u003c/h2\u003e \u003cp\u003eThe ECZ analysis for Cumbu from 2000 to 2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) reveals a relatively greater spatial stability compared to other cereals, although notable transitions occurred across decades.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the initial years (2000\u0026ndash;2005), cumbu exhibited strong performance with YECZ in 13 districts (\u0026asymp;\u0026thinsp;36%) and MECZ in 11 districts (\u0026asymp;\u0026thinsp;31%), AECZ in 6 districts (\u0026asymp;\u0026thinsp;17%) and NECZ in 7 districts (\u0026asymp;\u0026thinsp;19%). District such as Dharmapuri and Krishnagiri, Dindigul, Chengalpattu and Tenkasi districts demonstrated high yield efficiency, linked to adaptive crop management and local seed diversity.\u003c/p\u003e \u003cp\u003eDuring 2010\u0026ndash;2015, both MECZ (13 districts; \u0026asymp;36%) and NECZ (11 districts; \u0026asymp;31%) expanded, while YECZ declined to 9 district (\u0026asymp;\u0026thinsp;25%) and AECZ dropped to 4 districts (\u0026asymp;\u0026thinsp;11%). Declining cultivation area and changing land-use priorities were evident in districts such as Kancheepuram, Coimbatore, Namakkal, and Tiruchirappalli, contributing to NECZ. Dharmapuri, Krishnagiri and Pudukkottai districts maintained YECZ status, reflecting consistent yield performance.\u003c/p\u003e \u003cp\u003eBy 2020\u0026ndash;2025, NECZ expanded to 14 districts (\u0026asymp;\u0026thinsp;39%), indicating reduced area and productivity in several interior districts. MECZ declined to 10 districts (\u0026asymp;\u0026thinsp;28%), while YECZ remained stable in 9 districts (\u0026asymp;\u0026thinsp;25%) and AECS persisted in 4 districts (\u0026asymp;\u0026thinsp;11%). District such as Madurai, Theni, Kanyakumari, Dharmapuri and Krishnagiri continued to sustain yield efficiency, whereas Coimbatore, Eorde, Tiruppur and Ramanathapuram showed widespread NECZ due to land-use change, crop preference shifts or climatic stress.\u003c/p\u003e \u003cp\u003eDespite its drought tolerance, NECZ expansion after 2016 reflected the cumulative impact of erratic SWM rainfall and reduced early-season moisture essential for cumbu establishment.\u003c/p\u003e \u003cp\u003eAcross 25-year period, cumbu shows an gradual shift from YECZ toward both MECZ and NECZ, reflecting a variable performance across regions. Delta districts like Thanjavur, Nagapattinam and Mayiladuthurai remain less suitable for cumbu, whereas southern and north-western dry tracts continue to support the crop under resource constraints. Strengthening cumbu cultivation will require drought‑tolerant varieties, soil nutrient management, rainwater harvesting, and millet‑based intercropping systems to enhance resilience.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.8 Ragi (Finger millet)\u003c/h2\u003e \u003cp\u003eThe ECZ analysis for ragi from 2000 to 2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) indicates a balanced yet shifting pattern, reflecting the crop\u0026rsquo;s adaptability to semi‑arid environments and its sensitivity to land‑use and climatic changes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDuring 2000\u0026ndash;2005, ragi exhibited strong performance with 11 districts (\u0026asymp;\u0026thinsp;31%) under MECZ and 12 districts (\u0026asymp;\u0026thinsp;33%) under YECZ. AECZ accounted for 3 districts (\u0026asymp;\u0026thinsp;8%) and NECZ observed in 11 districts (\u0026asymp;\u0026thinsp;31%). High performing districts included Kallakurichi, Ranipet and Tenkasi districts, while Dharmapuri and Krishnagiri maintained yield efficiency. Districts such as Namakkal, Coimbatore, Perambalur and Pudukkottai showed low performance.\u003c/p\u003e \u003cp\u003eDuring 2010\u0026ndash;2015, MECZ expanded to 13 districts (\u0026asymp;\u0026thinsp;36%), particularly in Kallakurichi, Erode, and Thiruvarur. YECZ covered 11 districts (\u0026asymp;\u0026thinsp;31%), including Vellore, Thanjavur, and Theni. AECZ remained minimal (\u0026asymp;\u0026thinsp;6%), restricted to Dharmapuri and Krishnagiri, NECZ persisted in 11 districts (\u0026asymp;\u0026thinsp;31%), notably in Namakkal, Coimbatore, and Pudukkottai indicating continued challenges.\u003c/p\u003e \u003cp\u003eBy 2020\u0026ndash;2025, ragi showed a clear shift toward yield efficiency, with YECZ expanding to 15 districts (\u0026asymp;\u0026thinsp;42%) owing to Vellore, Dindigul, Virudhunagar, Tirunelveli, and Kanyakumari, where integrated millet promotion programs and improved varieties endorsed yield performance. MECZ declined sharply to 4 districts (\u0026asymp;\u0026thinsp;11%), while ACEZ increased to 5 districts (\u0026asymp;\u0026thinsp;14%), particularly in Dharmapuri, Krishnagiri, and Salem. NECZ spread to 13 districts, including Coimbatore, Namakkal, Perambalur, and Theni, reflecting ongoing challenges.\u003c/p\u003e \u003cp\u003eYield-efficient districts corresponded with improved monsoon performance during 2019\u0026ndash;2020, while NECZ pockets in interior districts reflected prolonged dry spells during 2012\u0026ndash;2016.\u003c/p\u003e \u003cp\u003eOverall, ragi shows a westward and southward stabilization over the 25 years, with a decline in North-eastern and delta regions. District such as Kallakurichi, Tenkasi, Dindigul and Tirunelveli districts consistently maintained MECZ and YECZ status, underscoring their suitability for millet based system. Strengthening ragi cultivation will require climate‑resilient varieties, improved soil moisture management, and value‑addition initiatives to enhance both productivity and livelihood resilience.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.9 Black gram\u003c/h2\u003e \u003cp\u003eThe ECZ classification for Black gram from 2000 to 2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) shows a clear progressive improvement in cropping efficiency, with several districts transitioning from NECZ to YECZ over time.\u003c/p\u003e \u003cp\u003eDuring the initial period (2000\u0026ndash;2005), black gram showed high vulnerability with NECZ dominating in 15 districts (\u0026asymp;\u0026thinsp;42%). MECZ covered 11 districts (\u0026asymp;\u0026thinsp;31%), while YECZ and AECZ accounted for 6 (\u0026asymp;\u0026thinsp;17%) and 5 districts (\u0026asymp;\u0026thinsp;14%), respectively. High-performing MECZ districts included Chengalpattu, Kallakurichi, Ranipet, Tirupatur, Salem, Nilgris, Tiruppur, Tenkasi, Ariyalur, Mayiladuthurai and Tanjavur districts. Interior districts like Namakkal, Dindigul, Madurai, Virudhunagar, Villupuram and Dharmapuri were yield efficient, while coastal districts were area efficient due to rice \u0026ndash; pulse cropping system.\u003c/p\u003e \u003cp\u003eIn the second period (2010\u0026ndash;2015) blackgram exhibited significant recovery under YECZ expanding into 15 districts (\u0026asymp;\u0026thinsp;42%), while MECZ scaling up to 10 districts (\u0026asymp;\u0026thinsp;28%). Positively the NECZ declined sharply to 8 districts (\u0026asymp;\u0026thinsp;22%) indicating improved productivity and area stability. District such as Erode, Krishnagiri, Tiruchirappalli, and Pudukkottai districts shifted from NECZ to YECZ, reflecting the impact of pulse-based cropping intensification and improved varieties. AECZ persisted in the Thiruvarur, Thanjavur, Nagapattinam and Thoothukudi districts, where the rice fallow pulse cropping system is traditionally followed.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBy 2020\u0026ndash;2025, YECZ spread expanded to 16 districts (\u0026asymp;\u0026thinsp;44%), including districts like Namakkal, Dharmapuri, Madurai, and Kanyakumari. MECZ remained stable (9 districts. \u0026asymp;25%), persisting in Chengalpattu, Ranipet, Tirupatthur, and The Nilgiris. AECZ persisted in 5 districts (\u0026asymp;\u0026thinsp;14%), while NECZ declined to 7 districts (\u0026asymp;\u0026thinsp;19%), mainly in Ramanathapuram, Karur, Dindigul, and Theni, where moisture constrained productivity.\u003c/p\u003e \u003cp\u003eThe shift from NECZ to YECZ in many districts aligned with favourable NEM rainfall during 2010, 2019, and 2020, which supported rice-fallow pulse productivity.\u003c/p\u003e \u003cp\u003eOverall, black gram shows a strong shift from area‑based to yield‑based efficiency, with sustained performance in north‑eastern, western, and southern districts. Strengthening climate‑smart pulse technologies, short‑duration varieties, and rice‑fallow intensification can further enhance black gram productivity and smallholder resilience.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.10 Green gram\u003c/h2\u003e \u003cp\u003eThe ECZ classification of green gram crop in Tamil Nadu over the period of 25 years (2000\u0026ndash;2025) exhibits a dynamic shift toward yield dominance (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e) although several districts continue to face climatic and resource-related constraints.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDuring 2000\u0026ndash;2005, greengram saw a balance between MECZ and YECZ with equal distribution in 13 districts (\u0026asymp;\u0026thinsp;36%) each. AECZ observed in 6 districts (\u0026asymp;\u0026thinsp;17%) and NECZ in 5 districts (\u0026asymp;\u0026thinsp;14%). Strong MECZ performance was noted in Chengalpattu, Tiruvallur, Ranipet, Kallakurichi, Namakkal, Tiruppur, The Nilgiris, Ariyalur, Mayiladuthurai, Virudhunagar, Tenkasi and Salem, while central and northwestern districts were highly yield efficient. The NECZ pockets were concentrated in northern districts along with Coimbatore and Cuddalore.\u003c/p\u003e \u003cp\u003eIn the second period (2010\u0026ndash;2015), green gram crop\u0026rsquo;s MECZ declined to 9 districts (\u0026asymp;\u0026thinsp;25%), while YECZ slightly decreased to 11 (\u0026asymp;\u0026thinsp;31%), and NECZ expanded sharply to 13 (\u0026asymp;\u0026thinsp;36%), reflecting climatic instability and reduced area under pulses in favour of cash crops. AECZ remained in 4 districts, including Nagapattinam and Thoothukudi, where rice-pulse and rainfed pulse systems support area stability. Namakkal and Virudhunagar shifted from MECZ to AECZ, indicating simultaneous area expansion and yield reduction.\u003c/p\u003e \u003cp\u003eIn 2020\u0026ndash;2025, green gram ECZ showed a partial recovery with YECZ expanding to 15 districts (\u0026asymp;\u0026thinsp;42%), mainly in Northern and Western Zone districts like Dharmapuri, Krishnagiri, Erode, Perambalur, and Namakkal. ACEZ has also risen to 8 districts (\u0026asymp;\u0026thinsp;22%), marking their territorial stability in Nagapattinam, Thiruvarur, and Mayiladuthurai, where rice-pulse cropping system is followed. There was a further decrease in MECZ to 4 districts (\u0026asymp;\u0026thinsp;11%), while NECZ slightly increased to 10 districts (\u0026asymp;\u0026thinsp;28%), notably in Kancheepuram, Villupuram, and Ramanathapuram, where soil degradation and erratic monsoons become the primary barriers.\u003c/p\u003e \u003cp\u003eGreen gram efficiency improved in districts receiving above-normal NEM rainfall (2005, 2021), while NECZ persisted in regions affected by repeated early-season moisture deficits.\u003c/p\u003e \u003cp\u003eOverall, green gram efficiency demonstrates sensitivity to rainfall variability and land-use shifts. Strengthening short-duration varieties, moisture-conserving agronomy, and rice-fallow intensification will be critical for improving green gram performance in NECZ regions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.11 Red gram\u003c/h2\u003e \u003cp\u003eThe ECZ classification for red gram from 2000 to 2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e) reflects the crop\u0026rsquo;s strong adaptation to dryland ecosystems, while also highlighting increasing vulnerability in several interior districts.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDuring 2000\u0026ndash;2005, red gram exhibited moderate performance with MECZ in 16 districts (\u0026asymp;\u0026thinsp;44%), YECZ in 13 districts (\u0026asymp;\u0026thinsp;36%), AECZ in 5 districts (\u0026asymp;\u0026thinsp;14%) and NECZ in 3 districts (\u0026asymp;\u0026thinsp;8%). Districts such as Dharmapuri, Krishnagiri, and Kallakurichi sustained high productivity due to favourable red soils and moderate rainfall. Yield performance dominated in Thanjavur, Ramanathapuram, and Tirunelveli, while the limited NECZ (3 districts) highlighted the crop\u0026rsquo;s suitability to dryland farming.\u003c/p\u003e \u003cp\u003eBetween 2010\u0026ndash;2015, MECZ declined to 13 districts (\u0026asymp;\u0026thinsp;36%), while YECZ remained steady at 13 (\u0026asymp;\u0026thinsp;36%), and NECZ expanded sharply to 9 districts (\u0026asymp;\u0026thinsp;25%). AECZ dropped to just 2 districts (\u0026asymp;\u0026thinsp;6%), limited to Vellore and Madurai. This period showed a mixed scenario with many MECZ shifted to YECZ/AECZ and vice versa. The rapid expansion of NECZ despite pulse-focused development programmes, indicated emerging climatic and resource constraints.\u003c/p\u003e \u003cp\u003eIn 2020\u0026ndash;2025, a partial recovery was observed. YECZ expanded substantially to 18 districts (\u0026asymp;\u0026thinsp;50%), becoming the dominant category, while MECZ declined to 8 districts (\u0026asymp;\u0026thinsp;22%), while AECZ rose to 6 districts (\u0026asymp;\u0026thinsp;17%). Importantly, NECZ contracted to 5 districts (\u0026asymp;\u0026thinsp;14%), signifying yield recovery and better resource utilization. Area efficiency was notable in north-western districts and in Karur, Nagapattinam, and Madurai, whereas several central districts continued to show weak performance.\u003c/p\u003e \u003cp\u003eThe expansion of YECZ during 2020\u0026ndash;2025 corresponded with improved monsoon distribution, whereas NECZ districts reflected the prolonged dry spells of 2012\u0026ndash;2016.\u003c/p\u003e \u003cp\u003eOverall, red gram exhibited a gradual shift toward \u003cb\u003eyield-led efficiency\u003c/b\u003e across north-eastern, western, and southern districts over the 25-year period. This improvement may be attributed to enhanced rainfall use efficiency, improved seed technologies, and pulse intensification initiatives. However, deltaic tracts and select interior districts continue to face instability, likely due to land-use changes, competing crop preferences, and rainfall variability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e3.12 Comparative performance of Food crops in Tamil Nadu\u003c/h2\u003e \u003cp\u003eThe performance of the major food crops across Tamil Nadu over the 25 year period is summarised in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The observed spatial and temporal shifts across MECZ, YECZ, AECZ, and NECZ categories reflect the combined influence of rainfall variability, technological adoption, market forces, resource availability, and land‑use change.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCrop performance of major food crops of Tamil Nadu\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrop\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECZ Trend (2000\u0026ndash;2025)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKey Zones\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMajor Constraints\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOverall Performance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRice\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGradual decline in area efficiency with stable yield performance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDeltaic and semi-delta regions (Cauvery basin)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWater scarcity, urban expansion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModerately Efficient\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMaize\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrong upward trend with sustained MECZ dominance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWestern and central drylands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeat stress, soil nutrient fatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHighly Efficient\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSorghum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeclining trend due to area contraction and climatic variability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCentral dryland tracts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCrop substitution, rainfall irregularity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModerately Low\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCumbu (Pearl Millet)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStable MECZ and YECZ persistence across dry belts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNorthern and southern arid belts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUrbanization, weak market linkages\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHighly Stable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRagi (Finger Millet)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCyclical efficiency pattern with notable yield recovery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWestern uplands and southern hill slopes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClimate variability, shrinking cultivation area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eResilient and Adaptive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlack Gram (Urd Bean)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinuous improvement with expanding efficient zones\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWestern and northern agro-climatic regions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePest pressure, rainfall fluctuation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHighly Promising\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGreen Gram (Mung Bean)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVariable efficiency with yield gains in irrigated zones\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNorth-eastern and western transitional belts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTerminal drought, low soil moisture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModerately Stable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRed Gram (Pigeon Pea)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate yield efficiency gains and stable MECZ continuity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNorth-central and western dry tracts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMoisture stress, erratic rainfall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModerately Efficient\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRice, the state\u0026rsquo;s primary staple, showed a gradual shift from MECZ/YECZ to AECZ/NECZ in several interior districts during the recent decade, largely due to water scarcity, stagnated productivity, unseasonal rainfall, floods during seedling or harvest stages, and urban expansion. Frequent NEM deficits (especially 2012\u0026ndash;2016) and erratic SWM onset further weakened rice efficiency in non‑delta districts. In contrast, maize has strengthened its position, transitioning from YECZ to sustained MECZ dominance, particularly in western districts such as Namakkal, Salem, and Dindigul. Maize efficiency closely aligned with favourable SWM years (2007, 2010, 2017), while irrigated belts buffered the impacts of dry spells.\u003c/p\u003e \u003cp\u003eSorghum exhibited a marked decline, with many earlier YECZ and AECZ belts shifting into NECZ, especially in northern and central drylands, mainly due to the dominance of maize. The prolonged dry spells during 2012\u0026ndash;2016 and reduced early‑season moisture critically affected sorghum establishment. Cumbu remained relatively stable, with persistent MECZ/YECZ zones in Dharmapuri, Krishnagiri, and Tenkasi.\u003c/p\u003e \u003cp\u003eHowever, erratic SWM distribution after 2015 caused NECZ expansion in interior belts despite cumbu\u0026rsquo;s drought tolerance. Ragi expanded until 2010\u0026ndash;2020 but showed mild regression thereafter, though western uplands and southern slopes continued to support strong performance. Yield gains corresponded with improved monsoon years (2019\u0026ndash;2020), while NECZ pockets reflected repeated dry spells in the preceding decade.\u003c/p\u003e \u003cp\u003eAmong pulses, black gram showed the most notable improvement, with several NECZ districts transitioning into YECZ/MECZ. High NEM rainfall years (2010, 2019, 2020) supported rice‑fallow pulse productivity. Green gram displayed variable efficiency, with gains in irrigated belts but persistent NECZ pockets in moisture‑limited regions. Its sensitivity to early‑season rainfall deficits explains the instability in interior districts. Red gram maintained moderate efficiency, with stable MECZ continuity in north‑central and western dry tracts. Improved rainfall distribution during 2020\u0026ndash;2025 supported YECZ expansion, while earlier drought years constrained central districts.\u003c/p\u003e \u003cp\u003eOverall, the comparative assessment highlights the need to recognise emerging vulnerabilities and shifting crop suitability. These insights are essential for designing climate‑smart interventions and region‑specific diversification strategies to sustain productivity under evolving agro‑climatic conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e3.13 Crop Diversification recommendations for NECZ in for different crops\u003c/h2\u003e \u003cp\u003eNECZ districts represent areas where existing crop choices are no longer sustainable due to rainfall variability, groundwater depletion, soil moisture stress, and declining productivity. Diversification toward short‑duration, drought‑tolerant, and resource‑efficient crops is essential to enhance resilience and optimize land use. Crops consistently performing well in MECZ and YECZ, such as cumbu, ragi, black gram, and green gram, offer suitable alternatives for NECZ districts, especially where water‑intensive crops like rice and maize show declining efficiency.\u003c/p\u003e \u003cp\u003eSimilarly, NECZ regions for sorghum and cumbu may benefit from pulses or oilseeds that align better with local agro‑climatic conditions. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e provides district‑wise diversification options based on ECZ outcomes, highlighting suitable alternative crops and the rationale for each recommendation. These targeted interventions support climate‑smart planning and help stabilize productivity in vulnerable regions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRecommendations for NECZ in Tamil Nadu\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrop\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistricts under NECZ (2020\u0026ndash;2025)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSuggested Alternative Crops\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAgro Climatic and Soil related Justification\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRice\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoimbatore, Karur\u003c/p\u003e \u003cp\u003eVirudhunagar, Thoothukudi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMillets (Cumbu, Ragi), Pulses (Cowpea, Green gram), Groundnut, Sesame\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRed and sandy loam soils with limited irrigation; low to moderate rainfall (\u0026lt;\u0026thinsp;800 mm); suited for dryland diversification and short-duration crops.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMaize\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKancheepuram, Tiruvannamalai, Coimbatore, Karur, Thiruvarur, Theni, Ramanathapuram, Sivagangai, Tirunelveli\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePulses (Black gram, Green gram), Oilseeds (Groundnut, Sesame), Sorghum, Cotton\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSemi-arid tracts with red soils and erratic rainfall; suitable for short-duration, drought-tolerant crops and mixed farming systems.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSorghum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTiruvallur, Cuddalore, Villupuram, Vellore\u003c/p\u003e \u003cp\u003eTiruvannamalai, Krishnagiri, Coimbatore, Erode, Perambalur, Ariyalur, Pudukkottai, Thanjavur, Thiruvarur, Madurai, Ramanathapuram, Sivagangai, Tirunelveli, The Nilgiris\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFinger Millet, Maize, Sunflower, Groundnut, Cotton, Vegetables (hill zones)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdaptable to red loam and black soils; suitable for 600\u0026ndash;1000 mm rainfall and temperature-tolerant systems; promotes income diversification.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCumbu (Pearl Millet)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKancheepuram, Namakkal, Coimbatore, Tiruppur, Erode, Tiruchirappalli, Karur, Perambalur, Pudukkottai, Thanjavur, Dindigul, Ramanathapuram, Sivagangai, Tirunelveli\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePulses (Black gram, Cowpea), Oilseeds (Groundnut, Sesame, Castor), Maize, Cotton\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePerforms better in dry, sandy loam to clay loam soils with low rainfall; ensures higher yield stability and economic resilience in dryland conditions.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRagi (Finger Millet)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKancheepuram, Cuddalore, Villupuram, Tiruvannamalai, Namakkal, Coimbatore, Perambalur, Ariyalur, Pudukkottai, Thiruvarur, Madurai, Theni, The Nilgiris\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaize, Sorghum, Groundnut, Pulses, Vegetables (hill zones), Sunflower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRed loam and lateritic soils with 600\u0026ndash;900 mm rainfall; suited for short-season or high-value crops under rainfed and semi-arid ecosystems.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlack Gram (Urd Bean)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTiruppur, Karur, Nagapattinam, Theni, Dindigul, Ramanathapuram, Virudhunagar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGreen gram, Cowpea, Groundnut, Sesame\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThrives in sandy loam to clay loam soils with moderate moisture; suitable as a rotation crop in rainfed tracts; enhances system resilience.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGreen Gram (Mung Bean)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKancheepuram, Villupuram, Tiruppur, Tiruchirappalli, Karur, Thanjavur, Madurai, Ramanathapuram, Virudhunagar, Tirunelveli\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShort-duration Pulses (Black gram, Cowpea), Millets, Oilseeds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePerforms well in sandy loam soils with residual moisture; ideal for post-rainy season cropping under limited irrigation and rainfed systems.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRed Gram (Pigeon Pea)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTiruchirappalli, Perambalur, Pudukkottai, Thiruvarur, Dindigul\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMillets (Cumbu, Ragi), Green gram, Groundnut, Sunflower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSuitable for intercropping in red loam and gravelly soils; better moisture utilization in 600\u0026ndash;800 mm rainfall zones; enhances soil fertility.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e3.14 Climate linked interpretation\u003c/h2\u003e \u003cp\u003eThe long-term ECZ assessment clearly demonstrates that cropping efficiency in Tamil Nadu is strongly shaped by rainfall variability, monsoon behaviour, and resource constraints. Districts that experienced stable or improving monsoon rainfall particularly during the inter-decadal recovery years (2007\u0026ndash;2008, 2010, 2019\u0026ndash;2020) showed positive transitions toward YECZ and MECZ across rice, maize, black gram, and ragi. In contrast, districts affected by severe rainfall deficits, such as during the 2016 drought, consistently shifted toward NECZ, especially for water-intensive crops like rice and for climate-sensitive pulses such as red gram and green gram.\u003c/p\u003e \u003cp\u003eThe persistence of NECZ in several interior and western districts highlights the need for climate responsive diversification strategies. Millets (cumbu, ragi) and pulses (black gram, green gram) demonstrated greater resilience in dryland belts, aligning with earlier findings on their superior drought tolerance and water-use efficiency (Negri et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Harish et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The ECZ framework thus provides a practical decision support tool for identifying districts where crop substitution, varietal improvement, or resource-conserving agronomy is essential.\u003c/p\u003e \u003cp\u003eThe results also underscore the importance of integrating agro-climatic indicators rainfall variability, groundwater status, and soil moisture regimes into district-level planning. As highlighted in earlier studies (Pazhanivelan et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Shunmugapriya et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), climate-informed zoning enables targeted interventions such as drought-tolerant cultivars, micro-irrigation, and soil health restoration. The ECZ transitions observed in this study reinforce the need for periodic updates to cropping recommendations, ensuring that agricultural planning remains aligned with evolving climatic realities and farmer resource conditions.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe synthesis of rainfall trends (2000\u0026ndash;2025) with ECZ transitions reveals strong climate sensitivity across Tamil Nadu\u0026rsquo;s major food crops. The state experienced pronounced interannual variability, with annual rainfall ranging from 598 mm (2016) to 1401 mm (2021), and a marked increase in rainfall during 2020\u0026ndash;2025. These fluctuations were mirrored in the spatial dynamics of cropping efficiency.\u003c/p\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Influence of rainfall variability on ECZ transitions\u003c/h2\u003e \u003cp\u003eDistricts receiving consistent or above normal rainfall during key years such as 2007, 2008, 2010, 2019, and 2020 showed improvements in YECZ and MECZ classifications for rice, maize, black gram, and ragi. Conversely, the severe drought of 2016, characterized by the lowest annual rainfall and a highly deficient Northeast Monsoon, corresponded with widespread NECZ expansion across rice, sorghum, cumbu, and pulses. These patterns reinforce the dominant role of monsoon rainfall in determining crop establishment, yield stability, and area persistence, consistent with earlier findings (Murugan \u0026amp; Madhumitha \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Pazhanivelan et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Crop-specific climate sensitivities\u003c/h2\u003e \u003cp\u003eRice and maize exhibited strong dependence on irrigation and monsoon stability. Deltaic districts with canal irrigation maintained AECZ or YECZ status across decades, while interior districts with declining groundwater shifted toward NECZ. Sorghum and cumbu, despite being dryland crops, showed declining efficiency in northern and deltaic districts due to erratic rainfall and land-use shifts, echoing earlier observations on climate-induced millet vulnerability (Negri et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Pulses displayed contrasting trends, black gram showed notable improvement, transitioning from NECZ to YECZ in many districts, while red gram and green gram remained highly sensitive to rainfall variability and soil moisture stress. These findings align with previous studies emphasizing the need for moisture-conserving agronomy and short-duration varieties in pulse systems (Jain et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Mukherjee et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Spatial patterns and agro-ecological gradients\u003c/h2\u003e \u003cp\u003eA consistent west\u0026ndash;east and north\u0026ndash;south gradient was observed across crops. Western and southern districts benefiting from better groundwater availability, hybrid adoption, and diversified cropping systems maintained MECZ/YECZ status for maize, ragi, and black gram. In contrast, northern and delta districts showed fluctuating efficiency due to rainfall variability, soil constraints, and competing crop choices. These spatial patterns corroborate earlier agro-climatic zonation studies (Rajkumar, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sathiyamurthi et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Implications for climate-resilient planning\u003c/h2\u003e \u003cp\u003eThe integration of rainfall trends with ECZ outcomes highlights the need for climate-resilient cropping strategies tailored to district-specific vulnerabilities. NECZ hotspots identified across cereals and pulses represent priority regions for diversification toward drought-tolerant millets, pulses, and oilseeds. Strengthening micro-irrigation, soil moisture conservation, and climate-resilient varieties will be essential to stabilize yields under increasing rainfall variability. Overall, the ECZ framework, when combined with long-term climate analysis, provides a robust foundation for climate-smart agricultural planning, enabling policymakers and extension systems to align crop recommendations with evolving agro-climatic realities.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Policy Recommendations","content":"\u003cp\u003eThe ECZ assessment highlights clear spatial differences in crop performance across Tamil Nadu, underscoring the need for climate-responsive, zone-specific interventions.\u003c/p\u003e \u003cp\u003e \u003cb\u003e5.1 Strengthen infrastructure in MECZ districts\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eEnhance irrigation reliability, canal maintenance, and groundwater recharge to sustain high productivity.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInvest in post-harvest infrastructures to reduce losses and stabilize farmer income.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePromote precision nutrient and water management to maintain long-term soil health.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e5.2 Expand extension support in YECZ districts\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePrioritize technology dissemination, including improved varieties, SRI/SSI methods, and integrated nutrient management.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStrengthen farmer training and advisory services to expand cultivated area and stabilize yields.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEncourage crop insurance uptake to buffer against rainfall variability.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e5.3 Target technological interventions in AECZ districts\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eIntroduce high-yielding, short-duration, and stress-tolerant cultivars to improve productivity.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePromote micro-irrigation, mulching, and soil moisture conservation practices.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSupport balanced fertilization and soil health restoration in nutrient-depleted regions.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e5.4 Diversify cropping systems in NECZ districts\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePromote millets (cumbu, ragi) and pulses (black gram, green gram, red gram) as climate-resilient alternatives to water-intensive crops.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEncourage intercropping and crop rotation to improve soil fertility and reduce climate risk.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIntegrate rainwater harvesting, farm ponds, and watershed interventions to enhance moisture availability.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e5.5 Integrate climate information into district planning\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eUse seasonal rainfall forecasts, drought indices, and ECZ maps to guide sowing decisions and crop advisories.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInstitutionalize periodic ECZ assessments to update cropping recommendations in line with evolving climatic trends.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStrengthen data-driven decision support systems for agriculture departments and extension networks.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis study provides a comprehensive 25 year assessment of Efficient Cropping Zones (ECZ) for major food crops in Tamil Nadu, integrating spatial crop performance with long-term rainfall variability. The results reveal clear shifts in cropping efficiency driven by monsoon fluctuations, groundwater stress, land-use change, and technological adoption. Deltaic districts maintained stable rice efficiency, while western drylands emerged as strong maize and millet belts. In contrast, several interior districts transitioned into NECZ, particularly during drought-affected years such as 2016.\u003c/p\u003e \u003cp\u003eMillets and pulses demonstrated notable resilience, reinforcing their suitability for climate-stressed dryland ecosystems. The ECZ framework proved effective in identifying vulnerability hotspots and guiding diversification strategies. Linking ECZ outcomes with rainfall trends underscores the importance of climate-informed planning, targeted interventions, and adaptive crop choices.\u003c/p\u003e \u003cp\u003eOverall, the study highlights the need for periodic ECZ monitoring, district-specific diversification, and climate-smart agronomy to sustain agricultural productivity under increasing climatic uncertainty. The insights generated here provide a robust foundation for policy formulation, extension planning, and long-term climate-resilient agricultural development in Tamil Nadu.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting Interests\u003c/h2\u003e \u003cp\u003e \u003cem\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/em\u003e \u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by Foreign Agency funded project of ICAR\u0026ndash;CRIDA and CIMMYT\u0026ndash;BISA, project titled \u0026ldquo;Atlas of Climate Adaptation for South Asia (ACASA)\u0026rdquo; and Department of Science and Technology, Government of India (GOI) through the project entitled \u0026ldquo;DST-NMSKCC-CEST Sponsored Centre of Excellence on Climate and Disaster Resilience Agriculture (DST/CCP/NMSKCC/CoE/237/2024). The first author Dheebakaran Ga is an Investigator in both the scheme.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eThe authors *Dheebakaran Ga and Raveendran M contributed to the study conception and design. Material preparation, data collection and analysis were performed by* all the authors *. The first draft of the manuscript was written by Dheebakaran Ga and all authors provided comment and corrections on previous versions of the manuscript. All authors read and approved the final manuscript.*\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis work was supported by Foreign Agency funded project of ICAR\u0026ndash;CRIDA and CIMMYT\u0026ndash;BISA, project titled \u0026ldquo;Atlas of Climate Adaptation for South Asia (ACASA)\u0026rdquo; and Department of Science and Technology, Government of India (GOI) through the project entitled \u0026ldquo;DST-NMSKCC-CEST Sponsored Centre of Excellence on Climate and Disaster Resilience Agriculture (DST/CCP/NMSKCC/CoE/237/2024). The first author Dheebakaran Ga is an Investigator in both the scheme.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analysed during the present study are not publicly accessible due to project‑level restrictions and portions of the dataset were sourced from the Tamil Nadu Government\u0026rsquo;s Seasonal Crop Report, which is restricted for open public use. However, they may be obtained from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAnnual Report 2018\u0026ndash;2019. Coimbatore: Directorate of Research, TNAU\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYadu A, Das GK (2021) Identification of efficient cropping zones for major field crops in Chhattisgarh, India. Int J Agricultural Sci Res 11(2):45\u0026ndash;53\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClimate Resilient Pulse Varieties for Tamil Nadu (2021) Department of Pulses. Tamil Nadu Agricultural University (TNAU), Coimbatore\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDivyadharshini S, Parkavi M, Pavendhan S, Pavithra S, Praveen Kumar P, Preetha E, Kumar P, Premalatha T, K., Chozhan K (2025) A comparative analysis of efficient cropping zones for sugarcane in Tamil Nadu, India using different indices. 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Madras Agricultural J 106(7\u0026ndash;9):478\u0026ndash;482\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShunmugapriya K, Selvi K, Ramya R (2021) Integration of multi-criteria decision analysis and GIS for agricultural site suitability in Tamil Nadu, India. Egypt J Remote Sens Space Sci 24(3):557\u0026ndash;565\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVision (2050) Indian Institute of Pulses Research, Kanpur. (2021) ICAR-IIPR. Indian Council of Agricultural Research\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"theoretical-and-applied-climatology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"taac","sideBox":"Learn more about [Theoretical and Applied Climatology](https://www.springer.com/journal/704)","snPcode":"704","submissionUrl":"https://submission.nature.com/new-submission/704/3","title":"Theoretical and Applied Climatology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Efficient Cropping zones, rainfall variability, food crops productivity, Spatio-temporal analysis","lastPublishedDoi":"10.21203/rs.3.rs-8716571/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8716571/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAgriculture in Tamil Nadu is strongly shaped by spatial and temporal climate variability, reflecting diverse agro‑climatic conditions and evolving resource constraints. Understanding the spatial performance of major food crops is essential for sustaining productivity in heterogeneous agro‑ecological regions. This study examines the spatio‑temporal dynamics of Efficient Cropping Zones (ECZ) for eight major food crops\u0026mdash;rice, maize, sorghum, pearl millet, finger millet, red gram, green gram, and black gram\u0026mdash;across Tamil Nadu over a 25‑year period (2000\u0026ndash;2025). District‑level area and yield data were used to compute the Relative Yield Index (RYI) and Relative Spread Index (RSI), classifying districts into Most Efficient (MECZ), Yield Efficient (YECZ), Area Efficient (AECZ), and Non‑Efficient Cropping Zones (NECZ).\u003c/p\u003e \u003cp\u003eResults reveal pronounced shifts in cropping efficiency driven by rainfall variability, monsoon fluctuations, groundwater depletion, soil fertility decline, and changing farmer preferences. Rice remained largely yield‑efficient in delta districts, while western and southern interior districts transitioned toward NECZ due to altered rainfall distribution and water stress. Maize showed expanding MECZ/YECZ zones supported by hybrid adoption and irrigation access, whereas sorghum and cumbu exhibited widespread efficiency decline linked to erratic monsoon performance. Millets retained resilience in traditional dryland belts, while pulses displayed contrasting trends, with black gram showing notable improvement and red/green gram exhibiting rainfall‑sensitive fluctuations. NECZ hotspots across multiple crops highlight priority districts for climate‑smart diversification toward drought‑tolerant millets, pulses, and oilseeds.\u003c/p\u003e \u003cp\u003eOverall, the study demonstrates the value of periodic ECZ‑based assessments as a climate‑informed decision‑support tool for optimizing resource allocation, guiding crop diversification, and strengthening climate‑resilient food systems in Tamil Nadu.\u003c/p\u003e","manuscriptTitle":"Climate Resilient Crop Zoning in Tamil Nadu, India: A 25 year assessment of major food crops","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-09 11:42:14","doi":"10.21203/rs.3.rs-8716571/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-03-09T14:40:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"73383154337009874196457068198590862393","date":"2026-02-09T13:12:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"140117089624157150192445055766781085364","date":"2026-02-04T13:07:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-04T12:21:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-29T22:52:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-29T22:52:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"Theoretical and Applied Climatology","date":"2026-01-28T05:14:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"theoretical-and-applied-climatology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"taac","sideBox":"Learn more about [Theoretical and Applied Climatology](https://www.springer.com/journal/704)","snPcode":"704","submissionUrl":"https://submission.nature.com/new-submission/704/3","title":"Theoretical and Applied Climatology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"60e96d68-1503-471a-910c-0838a96d974c","owner":[],"postedDate":"February 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-09T11:42:15+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-09 11:42:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8716571","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8716571","identity":"rs-8716571","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}