Influence Crop Yield Research Articles

Prediction of Soil Water Content and Electrical Conductivity Using Random Forest Methods with UAV Multispectral and Ground-Coupled Geophysical Data

The volumetric water content (VWC) of soil is a critical parameter in agriculture, as VWC strongly influences crop yield, provides nutrients to plants, and maintains the microbes that are needed for the biological health of the soil. Measuring VWC is difficult, as it is spatially and temporally heterogeneous, and most agricultural producers use point measurements that cannot fully capture this parameter. Electrical conductivity (EC) is another soil parameter that is useful in agriculture, since it can be used to indicate soil salinity, soil texture, and plant nutrient availability. Soil EC is also very heterogeneous; measuring EC using conventional soil sampling techniques is very time consuming and often fails to capture the variability in EC at a site. In contrast to the point-based methods used to measure VWC and EC, multispectral data acquired with unmanned aerial vehicles (UAV) can cover large areas with high resolution. In agriculture, multispectral data are often used to calculate vegetation indices (VIs). In this research UAV-acquired VIs and raw multispectral data were used to predict soil VWC and EC. High-resolution geophysical methods were used to acquire more than 41,000 measurements of VWC and 8000 measurements of EC in 18 traverses across a field that contained 56 experimental plots. The plots varied by crop type (corn, soybeans, and alfalfa) and drainage (no drainage, moderate drainage, high drainage). Machine learning was performed using the random forest method to predict VWC and EC using VIs and multispectral data. Prediction accuracy was determined for several scenarios that assumed different levels of knowledge about crop type or drainage. Results showed that multispectral data improved prediction of VWC and EC, and the best predictions occurred when both the crop type and degree of drainage were known, but drainage was a more important input than crop type. Predictions were most accurate in drier soil, which may be due to the lower overall variability of VWC and EC under these conditions. An analysis of which multispectral data were most important showed that NDRE, VARI, and blue band data improved predictions the most. The final conclusions of this study are that inexpensive UAV-based multispectral data can be used to improve estimation of heterogenous soil properties, such as VWC and EC in active agricultural fields. In this study, the best estimates of these properties were obtained when the agriculture parameters in a field were fairly homogeneous (one crop type and the same type of drainage throughout the field), although improvements were observed even when these conditions were not met. The multispectral data that were most useful for prediction were those that penetrated deeper into the soil canopy or were sensitive to bare soil.

16S rRNA Gene-Based Metagenomic Analysis of Rhizosphere Soil Bacteria in Arkansas Rice Crop Fields

The rhizomicrobiome is composed of microbes that live in association with plant roots. From nutrient cycling to carbon sequestration, soil microorganisms have provided a solid base for natural and agricultural ecosystems to function. The relationship between plant roots and soil microorganisms is especially relevant in food staples such as rice (Oryza sativa L.), as the various properties of these microbes can influence crop yield and plant health, thereby affecting a major portion of the food supply for an ever-growing world population. In this study, we used 16S rRNA gene-based metagenomic analysis to investigate the impact of crop rotation and soil cultivation methods (no-till or tillage) on rhizosphere bacterial diversity and composition in eight crop fields in Arkansas. Illumina MiSeq sequencing revealed 56 Phyla, with four major Phyla: Proteobacteria, Acidobacteria, Actinobacteria, and Bacteroidetes. Soil microbial communities in the samples studied were phylogenetically diverse but with a stable community structure. Crop rotation and tillage did not significantly affect bacterial diversity.

Cold stress and freezing tolerance negatively affect the fitness of Arabidopsis thaliana accessions under field and controlled conditions

Main conclusionHigher acclimated freezing tolerance improved winter survival, but reduced reproductive fitness of Arabidopsis thaliana accessions under field and controlled conditions.Low temperature is one of the most important abiotic factors influencing plant fitness and geographical distribution. In addition, cold stress is known to influence crop yield and is therefore of great economic importance. Increased freezing tolerance can be acquired by the process of cold acclimation, but this may be associated with a fitness cost. To assess the influence of cold stress on the fitness of plants, long-term field trials over 5 years were performed with six natural accessions of Arabidopsis thaliana ranging from very tolerant to very sensitive to freezing. Fitness parameters, as seed yield and 1000 seed mass, were measured and correlation analyses with temperature and freezing tolerance data performed. The results were compared with fitness parameters from controlled chamber experiments over 3 years with application of cold priming and triggering conditions. Winter survival and seed yield per plant were positively correlated with temperature in field experiments. In addition, winter survival and 1000 seed mass were correlated with the cold-acclimated freezing tolerance of the selected Arabidopsis accessions. The results provide strong evidence for a trade-off between higher freezing tolerance and reproductive fitness in A. thaliana, which might have ecological impacts in the context of global warming.

Grapevine rootstock and soil microbiome interactions: Keys for a resilient viticulture.

Soil microbiota has increasingly been shown to play an integral role in viticulture resilience. The emergence of new metagenomic and culturomic technologies has led to significant advances in the study of microbial biodiversity. In the agricultural sector, soil and plant microbiomes have been found to significantly improve resistance to environmental stressors and diseases, as well as influencing crop yields and fruit quality thus improving sustainability under shifting environments. Grapevines are usually cultivated as a scion grafted on rootstocks, which are selected according to pedoclimatic conditions and cultural practices, known as terroir. The rootstock connects the surrounding soil to the vine’s aerial part and impacts scion growth and berry quality. Understanding rootstock and soil microbiome dynamics is a relevant and important field of study, which may be critical to improve viticulture sustainability and resilience. This review aims to highlight the relationship between grapevine roots and telluric microbiota diversity and activity. In addition, this review explores the concept of core microbiome regarding potential applications of soil microbiome engineering with the goal of enhancing grapevine adaptation to biotic and abiotic stress.

Yield response of field beans (Vicia faba) to plant population and sowing date in a temperate climate

Abstract Sowing date and seed rate influence crop establishment, growth, yield and profitability. The growth and yield of field beans (Vicia faba) in response to sowing date and seed rate was examined over three seasons, 2016–2019, in Teagasc, Oak Park, Carlow, Ireland. Early winter sowings (October) established better than late winter sowings in November and January. No significant difference was found in establishment from mid-February to mid-March. Yield was generally highest from October sowings for the winter cultivar. Yields were similar from February, March and April sowings for the spring cultivar, with March generally yielding higher across the three seasons. Yield was also found to increase significantly with seed rate for both winter and spring cultivars. The economic optimum plant population was estimated for the October and March sowing dates, by fitting a standard (linear + exponential) curve. There is no published information on the optimum plant populations for field beans in Ireland and we believe we are the first to report these findings. The estimated economic optimum plant populations varied between 13 and 38 plants/m2 for both varieties, with an average optimum of 25.5 plants/m2. This range falls within the current recommendations for sowing field beans in Ireland, demonstrating that increasing plant populations above the current commercial practice for field beans in Ireland, will not increase yield or profitability.

Conservation agriculture influences crop yield, soil carbon content and nutrient availability in the rice–wheat system of north-west India

Context Tillage-based agriculture has led to soil health deterioration and decline in crop productivity. Recently, zero tillage (ZT) and crop residue management has emerged as an alternative to conventional tillage. Methods This experiment was done in north-west India over 3 years, with four treatments: (1) conventional transplanted puddle rice (TPR) + conventional tillage wheat (CTW) with 1/3 of wheat residues incorporated (TPR-CTWR1/3i); (2) TPR + CTW (TPR-CTW); (3) ZT direct-seeded rice (ZTDSR) + ZT wheat (ZTW) with 1/3 of wheat residues incorporated (ZTDSR-ZTWR1/3i); and (4) conventional tillage direct-seeded rice (CTDSR) + ZTW with full residues of both rice and wheat crop incorporated (CTDSR-ZTWRfr). Two rice (CSR 30, CSR 36) and two wheat (HD 2894, KRL 213) varieties were used. Soil samples were collected after harvest at 0–15 to 15–30 cm soil depth. Key results In rice, yield was significantly higher under conventional tillage, and variety CSR 36 outperformed CSR 30 in various yield attributes. In wheat, the number of grains per spike was significantly higher in TPR-CTWR1/3i than TPR-ZTW. After rice harvest, there was ∼10% and 5% higher available N in TPR-CTW and CTDSR-ZTWRfr compared to ZTDSR-ZTWR1/3i and TPR-CTWR1/3i, respectively (0–15 cm depth). After wheat harvest, highest SOC content (7.5 g kg−1) was found under CTDSR-ZTWRfr (0–15 cm depth); and highest total water-stable aggregates were observed under CTDSR-ZTWRfr (37.52%; 0–15 cm depth). Compared to farmers’ practise, the total global warming potential of rice–wheat cropping system was reduced by 43% with conservation agriculture-based management practises (ZTDSR-ZTWR1/3i). Conclusions DSR (in rice) and ZT in wheat with full residue retention best improved soil organic carbon and nutrient availability in soil. Implications Conservation agriculture systems can be adopted to improve crop productivity, soil health and reduce greenhouse gas emissions.

Structural properties of starch from single kernel of high-amylose maize

Cereal grain weight is an important agronomic character, influencing crop yield and quality. The high-amylose cereals usually have grains with different weights. However, it is unclear whether starches from kernels with different weights have different structural properties. In the research, the amylose content, amylopectin structure, crystallinity, and thermal properties of single-kernel starch were investigated in two high-amylose maize inbred lines, and the relationship between amylose/amylopectin content and kernel weight and the differences of starches from kernels with different weights were analyzed. The results showed that kernel weight had significantly positive relationship with amylose content and amylopectin B3+ chains (DP > 36) and average branch-chain length and negative relationship with amylopectin A chains (DP6-12) and B1 chains (DP13-24). The amylopectin A and B1 chains, relative crystallinity, and ordered degree had positive relationship with each other. The amylose content, amylopectin B3+ chains and average branch-chain length, and gelatinization temperature range were positively correlated with each other. Starches from kernels with different weights had different amylose contents, amylopectin structures, and thermal properties. The above results would offer references for breeding of high-amylose cereal crops and applications of grains with different weights.

Review on Macronutrient in Agronomy Crops

Macronutrients play a very important role in plant growth and development. Three main elements are nitrogen, phosphorus, and potassium (N, P, K) and are required in abundance. They must be readily available through soil medium or fertilizer. The secondary elements are sulfur, calcium, and magnesium (S, Ca, Mg). The problem of low soil fertility and poor plant nutrition does not only affect crop yields but also crop quality. Various nutrient elements influence biochemical processes and eventually affect the overall quality of various crops and their products. Depending on the amount that is available for plant uptake, these nutrients influence crop yields and quality and plants treated with absence of nutrients in the nutrient solution showed that N and Ca were the most limiting nutrients to biomass production The crop quality characteristics mostly reported to be affected by plant nutrition include: proteins, carbohydrate, sucrose and fructose content in grains, root crops, tuber crops and fruits; vitamins like beta-carotene content in fruits and tubers; moisture content at storage in cereal grains, potato tuber density; and frying colours, and fruit weight. It has been noted that essential and beneficial nutrient elements contribute to crop quality through functioning as raw materials for the synthesis of various plant components that have food value to humans and animals.

Influence of tied-ridge-furrow with inorganic fertilizer on grain yield across semiarid regions of Asia and Africa: A meta-analysis

BackgroundIn semiarid areas, low productivity of crops has been attributed to lack of appropriate soil moisture conservation practices since droughts and soil erosion are rampant in most areas of this region. Consequently, ridge-furrow rainwater harvesting is widely used in these regions across the globe. Despite ridge-furrow being widely practiced, tied-ridge-furrow has not been extensively adopted by small-scale farmers in semi-arid regions. Consequently, the effectiveness of tied-ridge-furrow as a viable method of increasing crop yield has received less attention.MethodologyFor large-scale implementation, a detailed assessment of how ridge furrow, tied–ridge-furrow with fertilizer, tied-ridge-furrow with mulching and tied-ridge-furrow without mulching or fertilizer influence crop yield in different agro-environments under varying climatic conditions is needed. This study used the PRISMA guidelines to determine the impact of tied-ridge-furrow rainwater harvesting technique with mulching or fertilizer on sorghum (Sorghum bicolor) and pearl millet (Pennisetum glaucum) grain yields.ResultsSorghum grain yield increased by 17% greater in tied-ridge-furrow without mulching or fertilizer in comparison to flat planting. This may be due to increase in soil organic carbon in the region (9 g kg−1). Grain yield of millet significantly increased by 20–40% in Africa from 18 study observations in tied-ridge-furrow with fertilizer application as compared to tied-ridge-furrow without mulching or fertilizer treatments. This might be due to the significant increase in total nitrogen by 13–42% in the soil at <50 mg kg−1 quantity which had an effect size of 469.14 [65.60, 872.67]. In terms of soil texture, grain yield of millet and sorghum significantly increased in heavy textured soils (clay loam, silt clay, and clay soils) with an effect size of 469.14 [65.60, 872.67] compared to light and medium-textured soils of zero effect sizes. Millet and sorghum grain yields in tied-ridge-furrow with mulching, on the other hand, were not significantly different from those in flat planting. This may be due to the mulching materials used in those tests.ConclusionIn view of yields of sorghum and millet increased significantly by 32% and 17% in tied-ridge-furrow without mulching or fertilizer treatment compared to flat planting and tied-ridge-furrow with fertilizer treatment compared with tied-ridge-furrow without mulching or fertilizer treatment, respectively, this study recommend the use of fertilizers in a tied-ridge-furrow system to increase grain yield in semiarid areas compared to flat planting. Again, the study recommends more research on tied-ridge-furrow systems with other organic mulches and fertilizers in semiarid areas.

ИЗМЕНЕНИЕ ПОЧВЕННОГО ПЛОДОРОДИЯ И УРОЖАЙНОСТИ КУКУРУЗЫ В ЗАВИСИМОСТИ ОТ СИСТЕМ ОСНОВНОЙ ОБРАБОТКИ

Tillage system is one of the factors that influences crop yield. The aim of the research was to determine the influence of the basic tillage systems on the change in soil fertility, yield and quality of corn grain in the soil and climatic conditions of the central zone of the Krasnodar Territory. The surveys were conducted in 2018–2020 on the experimental fields of the FSBSO “National Center of Grain named after P. P. Lukyanenko”. Soil – chernozems leached. All the experiments were carried out according to the standard methodology. In a stationary experiment, observations were performed to study several tillage practices: conventional tillage (25 cm depth plowing), mulch tillage with soil decompaction (reduced tillage done with a chisel plow to a depth of 32 cm for row crops), mulch tillage (deep tillage is excluded, disking to a depth of 10 cm twice or thrice is used instead). Plowing to a 25 cm depth improves the bulk of the soil in the 0–30 cm layer. However, chiseling to a depth of 32 cm and disking to a depth of 10 cm twice or thrice caused soil compaction. Standard tillage practice led to a decrease in the number of agronomically valuable aggregates (61.1 %) and their water resistance (59.4 %) compared to soil decompaction and minimum-tillage systems. The highest rates of productive moisture reserves were on the plots with traditional tillage and decompaction (140.6 and 141.5 mm, respectively, which is 14.7 % higher compared to the minimum mulching). The studied soil cultivation systems did not affect “1000-grain weight” but significantly affected the yield of grain from one ear (124.3 g) and the number of formed ears per one plant (1.04 pcs.). The corn yield on the fields with traditional and decompaction tillage methods was 56.9 and 55.9 c/ha, respectively; on minimum-tillage system, it decreased by 4.8 %. Protein content in grain harvested from the plots with traditional tillage practice was 11.4 %, which is higher compared to the minimum-tillage system. No significant differences were detected for crude ash and dry matter.

Crop yield forecasting and associated optimum lead time analysis based on multi-source environmental data across China

Accurate and timely crop yield forecasts can provide essential information to make conclusive agricultural policies and to conduct investments. Recent studies have used different machine learning techniques to develop such yield forecast systems for single crops at regional scales. However, no study has used multiple sources of environmental predictors (climate, soil, and vegetation) to forecast yields for three major crops in China. In this study, we adopted 7-year observed crop yield data (2013–2019) for three major grain crops (wheat, maize, and rice) across China, and three major data sets including climate, vegetation indices, and soil properties were used to develop a dynamic yield forecasting system based on the random forest (RF) model. The RF model showed good performance for estimating yields of all three crops with correlation coefficient (r) higher than 0.75 and normalized root means square errors (nRMSE) lower than 18.0%. Our results also showed that crop yields can be satisfactorily forecasted at one to three months prior to harvest. The optimum lead time for yield forecasting depended on crop types. In addition, we found the major predictors influencing crop yield varied between crops. In general, solar radiation and vegetation indices (especially during jointing to milk development stages) were identified as the main predictor for winter wheat; vegetation indices (throughout the growing season) and drought (especially during emergence to tasseling stages) were the most important predictors for spring maize; soil moisture (throughout the growing season) was the dominant predictor for summer maize, late rice, and mid rice; precipitation (especially during booting to heading stages) was the main predictor for early rice. Our study provides insights into practical crop yield forecasting and the understanding of yield response to environmental conditions at a large scale across China. The methods undertaken in this research can be easily implemented in other countries with available information on climate, soil, and vegetation conditions.

Evaluation of coastal farming under salinization and optimized fertilization strategies in China

Nitrogen (N) application and salinity are key factors influencing crop yield and net economic benefit in coastal saline-alkali soils. Integrated analysis and optimization of the benefits of wheat-corn cropping under different nitrogen applications in saline soils could provide lay the scientific basis for sustainable development of agriculture in coastal farmlands. A total of 571 pair-reviewed literature data on two-factor cross-over trials, involving soil salinity and nitrogen application, were integratively analyzed. Based on multi-objective optimization of crop yield, agronomic and net economic benefits, and soil nitrate residue in coastal saline-alkali soils, area-specific nitrogen application strategies were developed. The results showed that increasing the N application rate under 1.8–2.9‰ salinity can increase crop yield and economic benefits. The net economic benefit of crops was negative under 3.5‰ salinity. Above that threshold of 3.5‰, it is not suitable for planting food crops. Consequently, it is necessary to strengthen the management of saline-alkali soils. While the application rate of 2.78 × 108 kg N in winter wheat/summer corn cropping ensured environmental protection, farmers preferred 3.08 × 108 kg of nitrogen dose. These were respectively 40.4% and 33.9% lower than the traditional dose and with relatively higher benefits too.

Combining crop diversification practices can benefit cereal production in temperate climates

Diversifying cropping systems by increasing the number of cash and cover crops in crop rotation plays an important role in improving resource use efficiency and in promoting synergy between ecosystem processes. The objective of this study was to understand how the combination of crop diversification practices influences the performance of arable crop sequences in terms of crop grain yield, crop and weed biomass, and nitrogen acquisition in a temperate climate. Two field experiments were carried out. The first was a 3-year crop sequence with cereal or grain legume as the first crops, with and without undersown forage legumes and forage legume-grass crops, followed by a cereal crop. The second experiment was a 2-year crop sequence with cereal or legume as the first crops, a legume cover crop, and a subsequent cereal crop. For the first time, crop diversification practices were combined to identify plant-plant interactions in spatial and temporal scales. The results partly confirm the positive effect of diversifying cereal-based cropping systems by including grain legumes and cover crops in the crop sequence. Legume cover crops had a positive effect on subsequent cereal grain yield in one of the experiments. Using faba beans as the first crop in the crop sequence had both a positive and no effect on crop biomass and N acquisition of the subsequent cereal. In cover crops composed of a forage legume-grass mixture, the grass biomass and N acquisition were consistently increased after the grain legume, compared to the cereal-preceding crop. However, differences in the proportion of legume to grass in mixture did not influence crop yield or N acquisition in the subsequent cereal. In conclusion, these results support that increased crop diversity across spatial and temporal scales can contribute to resource-efficient production and enhance the delivery of services, contributing to more sustainable cropping systems.

Assessing alfalfa (Medicago sativa L.) tolerance to salinity at seedling stage and screening of the salinity tolerance traits.

Salt is among the most harmful agents that negatively influences crop yield. Alfalfa is an important perennial forage crop that exhibits wide cultivar variations in salt tolerance. Developing salt-tolerant alfalfa plants is a promising way to utilize salinized land. A comprehensive method was developed to achieve reliable and effective evaluation of alfalfa salt resistance. This included principal components, membership functions and cluster and stepwise regression analyses. These were used to analyse the salt tolerance coefficients of 14 traits and to evaluate 20 diverse alfalfa cultivars at the seedling stage. The various morphological root parameters of six alfalfa cultivars with contrasting salt tolerance were also tested by a scanning apparatus. According to the comprehensive evaluation value (D value), one highly salt-tolerant, two salt-tolerant, four moderately salt-tolerant and 13 salt-sensitive alfalfa cultivars were screened. A mathematical equation for the evaluation of alfalfa salt tolerance was established: D'=-0.126+0.667SFW+0.377SDW+1.089K+ /Na+ +0.172SFW/RFW (R2 =0.988; average forecast accuracy of 96.95%), where four indices were closely related to the salt tolerance: shoot fresh weight, ratio of shoot fresh weight to root fresh weight, shoot dry weight and ratio of K+ to Na+ in the shoot. We also found that SSA correlated strongly with SFW, SDW, K+ /Na+ , D values, while SRV correlated obviously with SFW, SFW/RFW and D values after 150mm NaCl treatment. In conclusion, the SFW, K+ /Na+ , SDW, SFW/RFW, SSA and SRV could be used as indicators of salt tolerance in alfalfa seedlings grown under 150mm NaCl treatment.

Effects of air pollutants and their interactive environmental factors on winter wheat yield

Quantifying the environmental determinants influencing crop yields is essential for crop management and ensuring global food security. However, comprehensive studies on the relative importance of multiple environmental factors and their interactions on crop yields during different phenological stages are still limited. In this study, we adopted a spatial heterogeneity detection method—geographic detector (GeoDetector)—to quantify how environmental factors, i.e., air pollutants, elevation, meteorological factors, and soil conditions, as well as their interactive effects, contributed to winter wheat yield. Data collected from agrometeorological stations in Henan Province, China, from 2014 to 2017 were analyzed as a case study. Results revealed that the dominant factors impacting winter wheat yield were elevation and soil acidity (pH). The interactions between elevation and soil conditions showed the strongest explanatory power throughout the growth period. Although air pollutants had relatively low independent impacts on yield, the interactions between air pollutants and other factors had significant nonlinear impacts. Contrary to traditional studies, ozone (O3) did not significantly impact winter wheat yield. In our study, carbon monoxide (CO) and sulfur dioxide (SO2) were the main air pollutants affecting yield at most growth stages, and the interactions between CO and elevation, pH, soil organic matter, and SO2 were significant. The effects of air pollutants on yield also changed across the growth stages, with the greatest impact observed from the three-leaf to tillering stages, and the weakest observed from the tillering to green-up stages. These findings improve our understanding of the relative importance of environmental factors on winter wheat yields, and have important implications for managing agricultural activities, improving crop models, and developing food security policies.

Economic Impacts of Thailand’s Biofuel Subsidy Reallocation Using a Dynamic Computable General Equilibrium (CGE) Model

For two decades, the Thai government has been promoting ethanol and biodiesel consumption through tax measures and price subsidies. Although this policy has substantially increased the consumption and production of biofuels, there is concern regarding its future fiscal burden. Due to fiscal constraints, the Thai government has planned to completely terminate the biofuel subsidy by 2022. This study aims at examining the economy-wide impacts of removing the biofuel subsidy and also conducting simulations of alternative scenarios, i.e., improving the yield of energy crops and reallocating the burden to expand capital investment in energy crop plantations. A recursive dynamic computable general equilibrium (CGE) model was used as the main quantitative method to conduct four simulation scenarios. This model was validated by comparing the simulation results with the actual 2015–2019 data and showed low values of root mean square error (RMSE). The simulation results indicate that solely terminating the price subsidy would lead to economy-wide contraction. Meanwhile, eliminating the price subsidy along with influencing crop yield improvement and expanding capital investment in energy crop plantations would lead to the lowest negative impacts. Therefore, the termination of the price subsidy should be simultaneously implemented with supply-side expansions.

Positive Effects of Crop Diversity on Productivity Driven by Changes in Soil Microbial Composition.

Intensive agriculture has major negative impacts on ecosystem diversity and functioning, including that of soils. The associated reduction of soil biodiversity and essential soil functions, such as nutrient cycling, can restrict plant growth and crop yield. By increasing plant diversity in agricultural systems, intercropping could be a promising way to foster soil microbial diversity and functioning. However, plant–microbe interactions and the extent to which they influence crop yield under field conditions are still poorly understood. In this study, we performed an extensive intercropping experiment using eight crop species and 40 different crop mixtures to investigate how crop diversity affects soil microbial diversity and activity, and whether these changes subsequently affect crop yield. Experiments were carried out in mesocosms under natural conditions in Switzerland and in Spain, two countries with drastically different soils and climate, and our crop communities included either one, two or four species. We sampled and sequenced soil microbial DNA to assess soil microbial diversity, and measured soil basal respiration as a proxy for soil activity. Results indicate that in Switzerland, increasing crop diversity led to shifts in soil microbial community composition, and in particular to an increase of several plant-growth promoting microbes, such as members of the bacterial phylum Actinobacteria. These shifts in community composition subsequently led to a 15 and 35% increase in crop yield in 2 and 4-species mixtures, respectively. This suggests that the positive effects of crop diversity on crop productivity can partially be explained by changes in soil microbial composition. However, the effects of crop diversity on soil microbes were relatively small compared to the effects of abiotic factors such as fertilization (three times larger) or soil moisture (three times larger). Furthermore, these processes were context-dependent: in Spain, where resources were limited, soil microbial communities did not respond to crop diversity, and their effect on crop yield was less strong. This research highlights the potential beneficial role of soil microbial communities in intercropping systems, while also reflecting on the relative importance of crop diversity compared to abiotic drivers of microbiomes and emphasizing the context-dependence of crop–microbe relationships.

Crop straw retention influenced crop yield and greenhouse gas emissions under various external conditions.

Crop straw retention is a strongly recommended practice for sustainable agricultural production in China. However, a comprehensive analysis of straw retention effects on crop yield, N2O and CH4 emissions, net greenhouse gas (NGHG), and net greenhouse gas intensity (NGHGI) and their response to various external influence factors, including location/climatic conditions, soil properties, and field management practices, in a national scale were easily ignored. Based on the collected published literatures, we found that straw retention improved crop yield and N2O and CH4 emissions by 4.7% (-4.6 to 25.8%), 18.3% (-26.6 to 57.6%), and 21.0% (-49.0 to 214.5%) in contrast with no-straw retention. For different external conditions, crop yield was increased by 15.9% in temperate zone and 10.7% in upland soils with straw retention. N2O emissions which correspond to the above conditions were enhanced by 42.2% and 18.8%, while CH4 emissions were restrained by 49.0% in temperate zone. Negligible changes in crop yield and N2O emissions were observed for subtropical zone or paddy soils, but with increase in CH4 emissions. Additionally, straw retention enhanced NGHG and NGHGI by 20.7% and 15.4% on average regardless of various external conditions, respectively. However, NGHG was reduced under conditions of straw retention in temperature or mulching to field. Straw retention under appropriate site-specially conditions simultaneously safeguard food security and slightly increase environmental effects.

Crop–weed relationships are context‐dependent and cannot fully explain the positive effects of intercropping on yield

Implementing sustainable weed control strategies is a major challenge in agriculture. Intercropping offers a potential solution to control weed pressure by reducing the resources available for weeds; however, available research on the relationship between crop diversity and weed pressure, and its consequences for crop yield is not yet fully conclusive. In this study, we performed an extensive intercropping experiment using eight crop species and 40 different species mixtures to examine how crop diversity affects weed communities and how the subsequent changes in weeds influence crop yield. Mesocosm experiments were carried out under field conditions in Switzerland and in Spain, which differ drastically in terms of climate, soil and weed community, and included monocultures, 2- and 4-species mixtures, and a control treatment without crops. Weed communities were assessed in terms of biomass, species number and evenness, and community composition. Results indicate that intercropping reduces weed biomass and diversity in Spain but not in Switzerland. In Switzerland, despite the lack of a crop diversity effect on weeds, crop yield increased with crop species number. Moreover, in Switzerland, where soil resources were abundant, increasing crop yield correlated with reduced weed biomass. In Spain, where water and nutrients were limited, crop yield was not related to weed biomass or diversity. The presented research applies plant community ecology in the context of agricultural crop production systems. We demonstrate that, in our study, increased crop yield in mixtures was not due to increased weed suppression in diverse crop communities, and so must be the result of other ecological processes. We further show that crop-weed relationships vary across environmental conditions; more specifically, our study shows that weeds are less detrimental to crop yield in harsher environments compared to benign abiotic conditions, where alternative strategies are needed to control weed pressure and ensure the yield benefits provided by intercropping.

Multi-temporal mapping of flood damage to crops using sentinel-1 imagery: a case study of the Sesia River (October 2020)

ABSTRACT Monitoring large-scale flood damage can be complicated and costly. Damages caused by floods affect also the agricultural sector. Permanence, height and quantity of stagnant water can significantly influence crop yield. Many studies exploit satellite data to map flooded areas, but only a few are focused on the timing of water persistence. This work refers to the river Sesia flooding event which occurred on 3 October 2020 in Northwest Italy with the aim of detecting damages to local crops. The analysis was based on Sentinel-1 data processed by Google Earth Engine platform. In particular, the Otsu’s method was applied to test the difference between pre- and post-event images. Areas that were mapped as flooded were successively analysed to estimate local water persistence: specifically, 1-2-6 days after the event. According to the available Corine Land Cover 2018 dataset, it was found that flood mainly affected agricultural areas (about 3288 ha). Since damage also relies on water persistence, a focus area was selected to test the effectiveness of S1 multi-temporal in mapping its distribution. Results show that only 3.5% of the agricultural fields in the focus area remained underwater for at least 6 days and 69% for only 1 day.