Productivity and Nutrient Balance of an Intensive Rice-Rice Cropping System Are Influenced by Different Nutrient Management in the Red and Lateritic Belt of West Bengal, India.

Rice is the lifeline for more than half of the world population, and in India, in view of its huge demand in the country, farmers adopt a rice-rice cropping system where the irrigation facility is available. As rice is a nutrient-exhausting crop, sustainable productivity of rice-rice cropping system greatly depends on appropriate nutrient management in accordance with the inherent soil fertility. The application of an ample dose of fertilizer is the key factor for maintaining sustainable rice yields and nutrient balance of the soil. Considering the above facts, an experiment was conducted on nutrient management in a rice-rice cropping system at the university farm of Visva-Bharati, situated in a sub-tropical climate under the red and lateritic belt of the western part of West Bengal, India, during two consecutive years (2014-2016). The experiment was laid out in a Randomized Completely Block Design with 12 treatments and three replications, with different rates of N:P:K:Zn:S application in both of the growing seasons, namely, kharif and Boro. The recommended (ample) dose of nutrients was 80:40:40:25:20 and 120:60:60:25:20 kg ha-1 of N:P2O5:K2O:Zn:S in the Kharif and Boro season, respectively. A high yielding variety, named MTU 7029, and a hybrid, Arize 6444 GOLD, were taken in the Kharif and Boro seasons, respectively. The results clearly indicated that the application of a recommended dose of nutrients showed its superiority over the control (no fertilizer application) in the expression of growth characters, yield attributes, yields, and nutrient uptake of Kharif as well as Boro rice. Out of the all treatments, the best result was found in the treatment where the ample dose of nutrients was applied, resulting in maximum grain yield in both the Kharif (5.6 t ha-1) and Boro (6.6 t ha-1) season. The corresponding yield attributes for the same treatment in the Kharif (panicles m-2: 247.9; grains panicle-1: 132.0; spikelets panicle-1: 149.6; test weight: 23.8 g; and panicle length: 30.6 cm) and Boro (panicles m-2: 281.6; grains panicle-1: 142.7; spikelets panicle-1: 157.2; test weight: 24.8 g; and panicle length: 32.8 cm) season explained the maximum yield in this treatment. Further, a reduction or omission of individual nutrients adversely impacted on the above traits and resulted in a negative balance of the respective nutrients. The study concluded that the application of a recommended dose of nutrients was essential for proper nutrient balance and sustainable yields in the rice-rice cropping system.

Multi-faceted impact and outcome of COVID-19 on smallholder agricultural systems: Integrating qualitative research and fuzzy cognitive mapping to explore resilient strategies.

The shock of Coronavirus Disease 2019 (COVID-19) has disrupted food systems worldwide. Such disruption, affecting multiple systems interfaces in smallholder agriculture, is unprecedented and needs to be understood from multi-stakeholder perspectives. The multiple loops of causality in the pathways of impact renders the system outcomes unpredictable. Understanding the nature of such unpredictable pathways is critical to identify present and future systems intervention strategies. Our study aims to explore the multiple pathways of present and future impact created by the pandemic and "Amphan" cyclonic storm on smallholder agricultural systems. Also, we anticipate the behaviour of the systems elements under different realistic scenarios of intervention. We explored the severity and multi-faceted impacts of the pandemic on vulnerable smallholder agricultural production systems through in-depth interactions with key players at the micro-level. It provided contextual information, and revealed critical insights to understand the cascading effect of the pandemic and the cyclone on farm households. We employed thematic analysis of in-depth interviews with multiple stakeholders in Sundarbans areas in eastern India, to identify the present and future systems outcomes caused by the pandemic, and later compounded by "Amphan". The immediate adaptation strategies of the farmers were engaging family labors, exchanging labors with neighbouring farmers, borrowing money from relatives, accessing free food rations, replacing dead livestock, early harvesting, and reclamation of waterbodies. The thematic analysis identified several systems elements, such as harvesting, marketing, labor accessibility, among others, through which the impacts of the pandemic were expressed. Drawing on these outputs, we employed Mental Modeler, a Fuzzy-Logic Cognitive Mapping tool, to develop multi-stakeholder mental models for the smallholder agricultural systems of the region. Analysis of the mental models indicated the centrality of "Kharif" (monsoon) rice production, current farm income, and investment for the next crop cycle to determine the pathways and degree of the dual impact on farm households. Current household expenditure, livestock, and soil fertility were other central elements in the shared mental model. Scenario analysis with multiple stakeholders suggested enhanced market access and current household income, sustained investment in farming, rapid improvement in affected soil, irrigation water and livestock as the most effective strategies to enhance the resilience of farm families during and after the pandemic. This study may help in formulating short and long-term intervention strategies in the post-pandemic communities, and the methodological approach can be used elsewhere to understand perturbed socioecological systems to formulate anticipatory intervention strategies based on collective wisdom of stakeholders.

Crop response to El Niño-Southern Oscillation related weather variation to help farmers manage their crops.

Although weather is a major driver of crop yield, many farmers don't know in advance how the weather will vary nor how their crops will respond. We hypothesized that where El Niño-Southern Oscillation (ENSO) drives weather patterns, and data on crop response to distinct management practices exists, it should be possible to map ENSO Oceanic Index (ENSO OI) patterns to crop management responses without precise weather data. Time series data on cacao farm yields in Sulawesi, Indonesia, with and without fertilizer, were used to provide proof-of-concept. A machine learning approach associated 75% of cacao yield variation with the ENSO patterns up to 8 and 24 months before harvest and predicted when fertilizer applications would be worthwhile. Thus, it's possible to relate average cacao crop performance and management response directly to ENSO patterns without weather data provided: (1) site specific data exist on crop performance over time with distinct management practices; and (2) the weather patterns are driven by ENSO OI. We believe that the principles established here can readily be applied to other crops, particularly when there's little data available on crop responses to management and weather. However, specific models will be required for each crop and every recommendation domain.

Macronutrient Management Effects on Nutrient Accumulation, Partitioning, Remobilization, and Yield of Hybrid Maize Cultivars.

It is critical to understand nutrient dynamics within different plant parts to correctly fine-tune agronomic advices, and to update breeding programs for increasing nutrient use efficiencies and yields. Farmer's field-based research was conducted to assess the effects of nitrogen (N), phosphorus (P), and potassium (K) levels on dry matter and nutrient accumulation, partitioning, and remobilization dynamics in three popular maize (Zea mays L.) hybrids (P3522, P3396, and Rajkumar) over two years in an alluvial soil of West Bengal, India. Experimental results revealed that NPK rates as well as different cultivars significantly (p ≤ 0.05) influenced the dry matter accumulation (DMA) in different plant parts of maize at both silking and physiological maturity. The post-silking dry matter accumulation (PSDMA) and post-silking N, P, and K accumulations (PSNA, PSPA, PSKA) were highest in cultivar P3396. However, cultivar P3522 recorded the highest nutrient remobilizations and contributions to grain nutrient content. Total P and K accumulation were highest with 125% of the recommended dose of fertilizer (RDF) while total N accumulation increased even after 150% RDF (100% RDF is 200 kg N, 60 kg P2O5, and 60 kg K2O ha-1 for the study region). Application of 125% RDF was optimum for PSDMA. The PSNA continued to increase up to 150% RDF while 125% RDF was optimum for PSPA. Cultivar differences significantly affected both remobilization efficiency (RE) and contribution to grain nutrient content for all tested macronutrients (N, P, and K). In general, RE as well as contribution to grain nutrient content was highest at 125% RDF for N and K, and at 100% RDF for P (either significantly or at par with other rates) for plots receiving nutrients. For all tested cultivars, nutrient remobilization and contribution to grain nutrient content was highest under nutrient-omission plots and absolute control plots. Both year and cultivar effects were non-significant for both grain and stover yields of maize. Application of 75% RDF was sufficient to achieve the attainable yield at the study location. The cultivar P3522 showed higher yield over both P3396 and Rajkumar, irrespective of fertilizer doses, although, the differences were not statistically significant (p ≥ 0.05). The study underscores the importance of maize adaptive responses in terms of nutrients accumulation and remobilization at different levels of nutrient availability for stabilizing yield.

Maize yield in smallholder agriculture system-An approach integrating socio-economic and crop management factors.

Yield gaps of maize (Zea mays L.) in the smallholder farms of eastern India are outcomes of a complex interplay of climatic variations, soil fertility gradients, socio-economic factors, and differential management intensities. Several machine learning approaches were used in this study to investigate the relative influences of multiple biophysical, socio-economic, and crop management features in determining maize yield variability using several machine learning approaches. Soil fertility status was assessed in 180 farms and paired with the surveyed data on maize yield, socio-economic conditions, and agronomic management. The C&RT relative variable importance plot identified farm size, total labor, soil factors, seed rate, fertilizer, and organic manure as influential factors. Among the three approaches compared for classifying maize yield, the artificial neural network (ANN) yielded the least (25%) misclassification on validation samples. The random forest partial dependence plots revealed a positive association between farm size and maize productivity. Nonlinear support vector machine boundary analysis for the eight top important variables revealed complex interactions underpinning maize yield response. Notably, farm size and total labor synergistically increased maize yield. Future research integrating these algorithms with empirical crop growth models and crop simulation models for ex-ante yield estimations could result in further improvement.

Macronutrients influence yield and oil quality of hybrid maize (Zea mays L.).

In the present two-year study, an attempt was made to estimate the grain yield, grain nutrient uptake, and oil quality of three commonly grown maize (Zea mays L.) hybrids fertilized with varied levels of nitrogen (N), phosphorus (P) and potassium (K). Results obtained from both the experimental years indicated that application of 125% of recommended dose of fertilizer (RDF) recorded maximum grain yield (10.37 t ha-1; 124% higher than control). When compared with 100% RDF, grain yield reduction with nutrient omission was 44% for N omission, 17% for P omission, and 27% for K omission. Nitrogen uptake was increased with increasing NPK levels up to 150% RDF that was statistically at par (p ≥ 0.01) with 125% RDF. Increasing trend in P and K uptake was observed with successive increase in NPK levels up to 125% RDF, above which it declined. The protein content was significantly higher in grains of var. P 3396 with 125% RDF. Nutrient management has significant (p ≤ 0.01) role in the grain oil content. Saturated fatty acids (palmitic, stearic and arachidic acid) content decreased, and unsaturated fatty acid (oleic, linoleic and linolenic acid) increased with increasing NPK levels. The average oleic acid desaturation and linoleic acid desaturation ratios were increased with increasing NPK levels up to 100 and 125% RDF, respectively. However, average monounsaturated fatty acids (MUFA): poly-unsaturated fatty acids (PUFA), saturated: unsaturated as well as linoleic: linolenic acid ratios were increased on receiving 75% RDF, and beyond that it showed decreasing trend. The omission of K had the highest inhibitory effect on corn oil quality followed by N and P omission.

Simultaneous analysis of free and conjugated estrogens, sulfonamides, and tetracyclines in runoff water and soils using solid-phase extraction and liquid chromatography-tandem mass spectrometry.

The ability to monitor multiple analytes from various classes of compounds in a single analysis can increase throughput and reduce cost when compared to traditional methods of analyses. This method for analyzing free (parent estrogen) and conjugated estrogens (metabolites) along with sulfonamides and tetracyclines utilizes a high pH (10.4) mobile phase with an ammonium hydroxide buffer for both positive- and negative-mode electrospray ionization. A single-step sample preparation by solid-phase extraction (SPE) was used to isolate and concentrate all analytes simultaneously. The analytical method was developed and validated for recoveries at 3 concentration levels for water and soil and produced recoveries of 42-123% and 21-105% respectively. Method detection limits ranged from 0.3 to 1.0 ng/L for water samples and 0.01 to 0.1 ng/g for soils. The method quantification limit ranged from 0.9 to 3.3 ng/L for water samples and 0.06 to 0.7 ng/g for soils. The single-point standard addition calibration procedure was validated across a linear range of MQL to 100 ng/L with ≥82% accuracy against a matrix matched standard curve. Furthermore, sorption of tetracyclines onto glassware was investigated and minimized by 10% using nitric acid-rinsed glassware, while separation parameters were further optimized based on retention time and signal responses. This method has been used for the quantification of estrogens, tetracyclines, and sulfonamides in soil and runoff waters with multiple compounds detected simultaneously in a single analysis.

Free and conjugated estrogen exports in surface-runoff from poultry litter-amended soil.

Land application of animal manures such as poultry litter is a common practice, especially in states with surplus manure. Past studies have shown that animal manure may contain estrogens, which are classified as endocrine-disrupting chemicals and may pose a threat to aquatic and wildlife species. We evaluated the concentrations of estrogens in surface runoff from experimental plots (5 x 12 m each) receiving raw and pelletized poultry litter. We evaluated the free (estrone, E1; 17beta-estradiol, E2beta; estriol, E3) and conjugate forms (glucuronides and sulfates) of estrogens, which differ in their toxicity. Sampling was performed for 10 natural storm events over a 4-mo period (April-July 2008). Estrogen concentrations were screened using enzyme-linked immunosorbent assay (ELISA), followed by quantification using liquid chromatography with tandem mass spectrometry (LC/MS/MS). Concentrations of estrogens from ELISA were much higher than the LC/MS/MS values, indicating crossreactivity with organic compounds. Exports of estrogens were much lower from soils amended with pelletized poultry litter than the raw form of the litter. No-tillage management practice also resulted in a lower export of estrogens with surface runoff compared with reduced tillage. The concentrations and exports of conjugate forms of estrogens were much higher than the free forms for some treatments, indicating that the conjugate forms should be considered for a comprehensive assessment of the threat posed by estrogens.