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Planting green manure to improve cash crop yield and soil health has been widely recognized, and understanding cash crop performance after green manure integration is pivotal for determining its potential to bolster and enhance crop productivity and sustainable production. However, it is unclear whether the effects of different types of green manure on subsequent cash crops are uniform. In order to clarify this issue, we systematically analyzed the effects of green manure types and nitrogen (N) application rates on succeeding cotton agronomic performance, yield, biomass, yield stability, and nutrient uptake. A split‐plot experiment with two factors was designed, main factor includes four cover cropping systems monoculture cotton (MC), February orchid/cotton cover cropping (FoC), hairy vetch/cotton cover cropping (HvC), and a mixture of February orchid and hairy vetch/cotton cover cropping (FHC), and sub‐main factor include four N application levels (0 (N0), 112.5 (N1), 168.75 (N2), and 225 (N3) kg N ha−1). Results suggests that nonlegume green manure (February orchid) accumulated more biomass, N, P, and K nutrients than the legume green manure (hairy vetch) and green manure mixture. Compared with cotton yield of MC, the FoC, HvC, and FHC system increased by 5.8%, 7.6%, and 15%, respectively. N use efficiency was more significantly influenced by the N application rates than by cropping systems. Specifically, as N application rates increased, N use efficiency decreased under MC, HvC, and FHC systems, while it increased under the FoC system. Additionally, we observed a trade‐off between cotton yield and yield stability, with the highest yield stability when cotton yield reached 2633 kg ha−1. This study provides evidence that nonlegume green manure (February orchid) with greater advantages on cotton vegetative organ growth, legume green manure (hairy vetch) can promote nutrient uptake compared to other green manure, while green manure mixture (February orchid and hairy vetch mixture) significantly increased cotton yield and yield stability. These findings provide evidence‐based insights highlighting the respective benefits of incorporating diverse species of green manure into cotton‐based cropping systems in the Yellow River Basin of China. [ABSTRACT FROM AUTHOR]

In dryland Mediterranean Vertisols, split nitrogen (N) application is usual in wheat crops. Because of the high clay content of these soils and the low rainfall, a single application might offer ecological and economic benefits without yield loss. We conducted a 5-year study as part of a long-term experiment and compared the split application of N (50% at tillering, 50% at stem elongation phase) with a single application (tillering) in 10 cropping systems resulting from the combination of type of cultivation (no-till and conventional tillage) and 2-year crop rotations (wheat-wheat, wheat-fallow, wheat-chickpea, wheat-faba bean and wheat-sunflower). Depending on the system × crop rotation interaction, a single application of 100 or 150 kg N ha-1 maintained grain yield, protein content and apparent N recovery, with no effect on nitrate content compared with a traditional split application. The average grain yield did not differ between split and single application of N (3.27 and 3.23 Mg ha-1, respectively, for single and split application of 100 kg N ha-1 rate; 3.46 and 3.40 Mg ha-1, respectively, for single and split application of 150 kg N ha-1 rate). The soil nitrate concentration at pre-seeding in the 0-0.3 m layer showed similar results, except in the case of the wheat-faba rotation, with lower nitrate concentration in the sub-subplots of single application and no-till. This work shows that adopting the single N application strategy in rotations on Mediterranean dryland Vertisols will reduce economic and environmental costs. [ABSTRACT FROM AUTHOR]

An experiment of integrated farming system (IFS) model comprising of 1.0 ha area was conducted during 2010-11 to 2018-19 at the Centre for Research on Integrated Farming Systems, Sardarkrushinagar, Dantiwada Agricultural University, Sardarkrushinagar of Gujarat for validation of an IFS model. There were four cropping system and allotted area was 0.70 ha, viz. castor (Ricinus communis L.) + greengram (Vigna radiate (L.) R. Wilczek] (0.32 ha); groundnut (Arachis hypogaea L.)- wheat (Triticum aestivum L.)-multicut fodder pearl millet [Pennisetum glaucum (L.) R. Br.] (0.08 ha); greengram - Indian mustard [Brassica juncea (L.) Czemj.]-pearlmillet (0.24 ha); and hybrid napier [Pennisetum purpureum (Schumach)] + fodder cowpea [Vigna unguiculata (L.) Walp.] - Lucerne (Medicago sativa L.) + fodder chicory (Cichorium intybus L.) (0.06 ha) based on small and marginal farm family requirement. N addition to that fruits and vegetable in 2 tiers were sown on 0.25 ha, making microbes-enriched vermin-compost from the waste and dung of the 2 buffaloes (Bubalus bubalis) reared on 0.04 ha. Farm wastes were recycled within the system which obliterated the need to purchase off-farm inputs. The internal bunds of cropping systems were used for growing fodder, while farm boundary with quick-growing timber tree. The model had a provision of farm pond (0.01 ha) for water harvesting and well recharging on low-lying depression of the farm. Groundnut - wheat - multicut F. Rajka Bajra + Horticultural and Vegetables crops +Live stock+ vermi compost + boundary plantation + farm pond registered significantly higher GEY (8696 kg/ha), which was statistically at par with IFS Model (Castor + Greengram (032 ha) + Groundnut - Wheat -Multicut F. Rijka Bajra (0.08 ha)+ Green gram -Mustard-Pearl millet (0.24 ha)+ Hy. Napier + Cowpea (F) - Lucerne + F. Chicory (0.06 ha)+Horticultural and Vegetables crops (0.25 ha) +Live stock(0.025 ha) + vermi compost (0.010 ha)+ boundary plantation + farm pond (0.015 ha) (7977 kg/ha) registered significantly higher employment generation (476 mandays/year). [ABSTRACT FROM AUTHOR]

[Display omitted] • AgrOptim is an extensive cropping system simulation optimization framework. • Crop and environmental risk simulation models are coupled with genetic algorithms. • Management practices that optimize different biophysical and economic objectives are identified. • Trade-offs between economic and biophysical indicators are simulated and quantified. • Sustainability gaps are quantified for three cropping systems in Argentina. Cropping systems should be designed to be more productive and have a smaller environmental footprint to sustainably meet the growing demand for food, fiber, and fuel. However, this requires the evaluation and ranking of many cropping system designs based on their economic and biophysical performance, which are often in conflict. Although field experiments and simple crop simulation models have been used for this purpose, studies have generally considered a limited number of agronomic decision combinations or indicators that partially capture ecosystem functions. Coupling evolutionary algorithms with process-based crop simulation models provides a less resource-intensive alternative and can incorporate many indicators to (1) quantify the trade-offs between biophysical and economic performance, and (2) identify the set of agronomic decision combinations that minimize these trade-offs. The objective of this paper was to present AgrOptim, a novel cropping system simulation optimization framework that uses genetic algorithms to optimize a holistic set of biophysical and economic performance indicators through different combinations of agronomic decision variables (i.e., crop sequence, crop structure, pesticide dose, and fertilizer dose). Indicators were derived from a process-based crop simulation model, an ecotoxicological risk simulation model, and emergy synthesis. The framework was implemented in Argentina to (1) characterize the relationship between economic and biophysical indicators and (2) evaluate the current state and potential improvements of three frequently used cropping system designs. A multi-objective optimization experiment was designed to simultaneously optimize 30-year cropping sequences based on one economic objective (return on investment) and four biophysical objectives (crop residue carbon inputs, precipitation use efficiency, nonrenewable to renewable energy ratio, and pesticide ecotoxicity). Results showed that trade-offs exist between economic and all biophysical objectives, albeit with varying intensities. Additionally, the decision variables that provided improved performance in terms of carbon residues, precipitation use efficiency, and ecotoxicological risk also presented higher levels of nonrenewable energy use. For the three frequently used cropping system designs, the decision variables that improved the performance of each indicator were identified. These findings highlight the challenges faced by agricultural producers considering the trade-offs between their economic and biophysical objectives. Additionally, they reveal potential model-aided improvements that can be obtained using crop simulation models and optimization algorithms to redesign cropping systems. [ABSTRACT FROM AUTHOR]

The current context of food security and global geopolitical crises calls for proactive efforts to seek adaptive strategies for limited resources in agriculture. The production of phosphatic-based fertilisers has caused a substantial depletion of natural phosphorus (P) reserves, raising concerns about price increases due to the growing demand for P. The aim of the study is to assess whether the use of liquid organo-mineral P-complexes can be an adaptive strategy to address the issue of the limited P-fertiliser resource. A complete randomised block design was implemented with three replicates, spanning two contrasting cropping seasons under a Mediterranean climate with reduced tillage and rainfed conditions. The study aimed to assess the response of a durum wheat–maize rotation to various rates of liquid organo-mineral P-complexes (humic-complexed phosphate; HCP) in comparison to granular triple superphosphate (TSP). The evaluation focused on several parameters, including P availability, plant architecture, dry matter accumulation, grain yield and yield components and P use efficiency (PUE) for both durum wheat and maize. The results revealed that applying HCP at a rate of 4 or 8 kg ha−1 increased soil P availability on average by 66% and 144%, respectively, compared to the control (no P-fertilisation), although a significant interaction with the monitoring year emerged. For wheat, applying HCP at a rate of 8 kg ha−1 of P resulted in higher grain yield (+15%), protein content (+0.9%) and P uptake (+48%) than the control on average considering both monitoring years. In the season characterised by favourable rainfall patterns, the application of HCP at 5 or 10 kg ha−1 of P for maize showed similar effects in terms of soil P availability, dry matter accumulation, grain yields and PUE. Conversely, in the season marked by a deficiency in summer precipitation, low PUE for maize was observed for HCP fertilisers, although they remained positive, unlike the case of TSP. Using HCP in conservation agriculture appears promising as an adaptive solution to address P-fertiliser scarcity, especially amid food security challenges and global crises. However, further studies are required to validate these findings in diverse pedo-climatic contexts and cropping systems. • Humic complexed P fertiliser (HCP) enhances soil P availability, especially at 0–10 cm depth. • HCP resulted in a general higher maize and wheat grain yield and crops P efficiency. • HCP is promising in the context of conservation agriculture. [ABSTRACT FROM AUTHOR]

Agricultural intensification, besides increasing land productivity, also affects weed communities. We studied weed shifts in cropping sequences differing in the identity and number of crops grown. We also evaluated whether dissimilar weed communities in different cropping systems converge towards more similar communities, when the same sequence is cropped during 2 years. In three locations in the Rolling Pampa, Argentina, field experiments were conducted including five cropping systems in the first year (winter cereal/soyabean, field pea/soyabean, and field pea/maize double crops, and maize and soyabean as single crops), while the same sequence was grown in the following 2 years (wheat/soyabean double crop and maize). Changes in weed community composition and structure were analysed through multivariate analyses and frequency-species ranking plots. Weed communities differed first among sites, while weed shifts within each site were mainly associated with growing season and crop type. Differences among crop sequences were higher in the first year, mostly related to specific crop grown, rather than to the number of crops in the sequences. Differences were reduced when the same sequence was grown during two consecutive seasons. Frequency of highly common weeds was negatively associated with the number of days with high crop cover. Our findings contribute to understand weed shifts in consecutive growing seasons, which may help readapting crop sequences to reduce the occurrence of abundant weed species. [ABSTRACT FROM AUTHOR]

Understanding the quantity and timing of labour to fulfill the goals of different cropping systems or crop rotations is critical, but poorly quantified and understood in many agricultural systems, including the grain-growing regions of eastern Australia. Yet, labour supply and demands are important considerations for farmers and can significantly influence their agronomic management and decisions to adopt modified crop rotation systems. Here, we investigated the extent to which crop rotation systems, that differed in their intensity (i.e. the proportion of time when crops were growing), and diversity (i.e. the range of crops grown) influence labour requirements and labour productivity. We used the Agricultural Production Systems sIMulator (APSIM) to simulate a set of different crop rotations and combined the output with farmer survey data and expert knowledge derived from farm advisers to compute the labour inputs for key crop operations (i.e. sowing, spraying, harvesting). This information was used to calculate the labour required and the timing of this demand for each cropping system. We showed that as the cropping intensity increases the labour demand also increases, and vice versa. However, only small differences in labour demands were identified between systems with differing crop diversity (i.e. range of crops grown). Thus, when it comes to labour demands, crop diversity is less critical than cropping intensity. Labour demand was highly seasonal, with peaks around the intense operations of sowing and harvesting. These peak demands constrained the area that could be managed by a unit of labour, particularly as the cropping intensity increased. Further, this analysis highlights that the most profitable systems may not necessarily be the most efficient in terms of labour productivity (i.e. return per unit of labour). This analysis shows that when labour is limiting, labour demands and especially peak periods may contribute to a farmer's choice of cropping systems, adding to other critical factors like risk aversion and profit maximisation. The analysis contributes to the literature on the role of labour in the context of influencing the implementation and adoption of what are seemingly more productive or profitable farming systems. In particular, the results demonstrate how labour as a critical farm resource (i.e. its quantity, seasonality and timing, and productivity) can influence the design of crop rotations. [Display omitted] • Many cropping systems in Australia are being modified by altering their intensities and crop diversity, but their labour demands are unknown. • Crop rotations with distinct intensity and diversity are simulated in APSIM to estimate their labour demands, seasonality, and economic returns. • Altering cropping intensity had stronger influence on labour demands and returns than changing the crop diversity in the rotation. • Labour demands between rotations is not substantial to influence a farmers decision on adopting alternative or modified cropping sequences. • Findings contribute to the growing discussion on the role of labour for the design and potential feasibility of innovative cropping systems. [ABSTRACT FROM AUTHOR]

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Highlights: [•] Wheat grain yield was increased after 1 year of rotation with soybean green manure. [•] Rotation with soybean decreased the fertilizer N requirement of subsequent wheat. [•] Growing soybean in the fallow period enhanced the subsequent wheat N and Zn. [•] Soil N and Zn supply capacity was improved by growing soybean as green manure. [Copyright &y& Elsevier]

Maize being an exhaustive crop demands for higher fertilizer application, especially N fertilizer and the addition of nutrients through fertilizers is, however, far below the crop removal. Exploring low - cost agronomic practices is highly imperative in the present day agriculture to increase farmers profitability and environmental safety. Further, while devising fertilizer N recommendations to a crop it is necessary to consider cropping sequence as a whole rather than that individual crop per se because the need for nutrients by a crop would vary depending upon the preceding crop type and its inputs usage. This review provides an update on the research undertaken on productivity and nitrogen requirement of maize as influenced by preceding cropping practices. [ABSTRACT FROM AUTHOR]

Abstract: Management and cropping systems varying in soil mobilization rates and plant-residue inputs may have profound effects on the biological properties of soil. Therefore, the objective of this study was to quantify soil microbial biomass carbon and nitrogen (MB-C and MB-N)—by means of the fumigation-extraction method—under varied soil-management and crop-rotation/succession systems in southern Brazil, correlating the results with yields of soybean and maize crops. The microbial biomass and grain yields were examined at the 0–10cm layer in four short- to long-term field experiments. Experiment 1 was a 26-year trial consisting of four soil-management systems: (1) no-tillage (NT), (2) conventional tillage [(CT) with disc plough], (3) field cultivator (FC) or (4) heavy-disc harrow (DH), each with a crop succession (CS) of soybean (summer) and wheat (winter). Experiment 2 was a 21-year trial consisting of one CS, soybean/wheat every year) and seven crop rotations (CRs) comprising soybean, maize, wheat and green manures (lupine, radish and black oat), under the NT system. Experiment 3 comprised a 14-year CT trial, and 4-year and 14-year NT trials, with both one CS and two CRs. Experiment 4, a 10-year trial consisted of CT and NT and three CRs. Analyses were performed during the summer and winter croppings. Differences in microbial parameters, as a function of crop succession and rotation, were not easily detected as they varied as a function of a complex combination of plant species and time of implementation of the experiment. In contrast, MB-C and MB-N values were consistently higher—up to more than 100%—under NT in comparison to CT and were associated with higher grain yields. Our results—from this wide range of experiments—suggest that MB-C and, particularly, MB-N are sensitive indicators of the effects of soil- and crop-management regimens. [ABSTRACT FROM AUTHOR]

The current understanding of the link between land management practices and GHG (greenhouse gas) emissions is limited in the small-scale farm sector of sub-Sahara regions due to insufficient or fragmented land-use data. Land-use categories recognized in the national GHG inventories in Kenya are coarse. Therefore, they do not adequately account for the diversity in small-scale land uses. Characterization of land-use and knowledge of key drivers of land-use change is necessary to improve national GHG inventories in the SSA (Sub-Sahara Africa) region. We implemented a cross-sectional survey to characterize land-use and determine factors which influenced changes in land use within small-scale farms of Tharaka-Nithi County, Kenya. We sampled 300 farmers using multistage sampling and collected crop sequence recall data at plot level for three years (seven seasons). We grouped crop sequences into clusters using the ' TraMineR' R package. We derived four clusters including banana, tea, and declining fallows (cluster 1, 19.2% of plots), cereal-legume systems (cluster 2, 55.1%), fodder (cluster 3, 11.7%) and coffee (cluster 4, 14.0%). We observed higher N application rates in perennial cropping systems, than in annual crops, including cereal-legume systems. We observed that farmers in higher potential agro-ecological zones, male-managed farms, with higher per capita land area, higher remittances and higher total house-hold incomes, were associated with a higher propensity to adjust crop enterprises, leading to more unstable land-use sequences. Contrariwise, farmers with higher education, credit access, secure land tenure, increasing slope, good soil fertility, and longer farming experiences recorded a lower propensity to adjust their land uses, resulting in more stable crop sequences. Farmer socio-demographic characteristics influenced land-use change, which is directly linked with soil GHG emissions. Our findings propose the adoption of Tier II GHG quantification approaches which disaggregate between annual and perennial crop enterprises. GHG emissions are likely to be more generalizable in stable perennial crop systems than annual systems. Thus, better disaggregation of GHG sampling in annual crop systems is needed due to high diversity in crop and soil fertility management, and the dynamic nature of C and N cycling in these systems. [ABSTRACT FROM AUTHOR]

This study was carried out to investigate the changes that may occur to the soil water holding capacity under center pivot irrigation systems when grown with different crop patterns over a long period of time. The changes of water holding capacity were checked as affected by crop location and depth. The study was carried out in a dominantly sandy loam soil irrigation scheme, north of Saudi Arabia in 1999. The field capacity (FC), permanent wilting point (PWP) were determined by the pressure membrane method. The general trend of the results showed that crop sequences that were fallow or had cereal crops in their rotation before sampling period considerably affected FC and PWP. This is represented by crop sequences 6, 5 and 2 which produced the highest means of FC at 14.75, 12.79 and 12.68%, respectively. Moreover, the lowest means of FC were produced with alfalfa dominating the crop rotation prior to the sampling period. This is represented by crop sequences 7, 3 and 4 at FCs of 9.56, 9.74 and 10.28%, respectively. Crop sequences 1,4,5 and 6 gave the highest values of PWP, while the lowest one was in crop sequence 7 (4.79%). The highest means of available water (AW) were found in crop sequences 6, 2, 5 at 8.65, 6.87 and 6.35%, respectively. While the lowest value of AW was found in crop sequence 4 at 3.69%. The results showed that the soil samples collected from inside center pivots, for all crop sequences, produced higher means of FC at 12.87%, PWP at 6.53 and 6.34% compared with soil samples collected from outside the center pivot. The relative decrease of FC, PWP and AW due to increasing the soil sample depth from 0–15 to 60–90 cm was 21.55, 22.52 and 20.53%, respectively. The measured values of FC, PWP and AW showed that the highest values of standard deviation (S.D.) and coefficient of variation (CV), for FC, PWP, and AW were found in soil sample depth followed by soil sample location and crop sequence respectively. The interaction effect of crop sequences and soil sample depths on PWP and AW was significant. [Copyright &y& Elsevier]