Multiple Cropping Research Articles

Aeluropus littoralis stress-associated protein promotes water deficit resilience in engineered durum wheat

Global climate change-related water deficit negatively affect the growth, development and yield performance of multiple cereal crops, including durum wheat. Therefore, the improvement of water-deficit stress tolerance in durum wheat varieties in arid and semiarid areas has become imperative for food security. Herein, we evaluated the water deficiency resilience potential of two marker-free transgenic durum wheat lines (AlSAP-lines: K9.3 and K21.3) under well-watered and water-deficit stress conditions at both physiological and agronomic levels. These two lines overexpressed the AlSAP gene, isolated from the halophyte grass Aeluropus littoralis, encoding a stress-associated zinc finger protein containing the A20/AN1 domains. Under well-watered conditions, the wild-type (WT) and both AlSAP-lines displayed comparable performance concerning all the evaluated parameters. Ectopic transgene expression exerted no adverse effects on growth and yield performance of the durum wheat plants. Under water-deficit conditions, no significant differences in the plant height, leaf number, spike length, and spikelet number were observed between AlSAP-lines and WT plants. However, compared to WT, the AlSAP-lines exhibited greater dry matter production, greater flag leaf area, improved net photosynthetic rate, stomatal conductance, and water use efficiency. Notably, the AlSAP-lines displayed 25 % higher grain yield (GY) than the WT plants under water-deficit conditions. The RT-qPCR-based selected stress-related gene (TdDREB1, TdLEA, TdAPX1, and TdBlt101-2) expression analyses indicated stress-related genes enhancement in AlSAP-durum wheat plants under both well-watered and water-deficit conditions, potentially related to the water-deficit resilience. Collectively, our findings support that the ectopic AlSAP expression in durum wheat lines enhances water-deficit resilience ability, thereby potentially compensate for the GY loss in arid and semi-arid regions.

IJAZ-based approach to engineer lepidopteran pest resistance in multiple crop species.

The fall armyworm (FAW) poses a significant threat to global crop production. Here we showed that overexpression of jasmonate ZIM-domain (JAZ) protein GhJAZ24 confers resistance to cotton bollworm and FAW, while also causing sterility in transgenic cotton by recruiting TOPLESS and histone deacetylase 6. We identified the NGR motif of GhJAZ24 that recognizes and binds the aminopeptidase N receptor, enabling GhJAZ24 to enter cells and disrupt histone deacetylase 3, leading to cell death. To overcome plant sterility associated with GhJAZ24 overexpression, we developed iJAZ (i, induced), an approach involving damage-induced expression and a switch from intracellular to extracellular localization of GhJAZ24. iJAZ transgenic cotton maintained fertility and showed insecticidal activity against cotton bollworm and FAW. In addition, iJAZ transgenic rice, maize and tobacco plants showed insecticidal activity against their lepidopteran pests, resulting in an iJAZ-based approach for generating alternative insecticidal proteins with distinctive mechanisms of action, thus holding immense potential for future crop engineering.

Impacts of High-Frequency Chicken Manure Biochar Application on N2O and CH4 Emissions from Vegetable Field in Subtropical China

Vegetable production in Subtropical China is distinguished by excessive nitrogen (N) fertilization, frequent irrigation, and multiple crop rotations in a single year. The aforementioned variables are closely related to soil nitrous oxide (N2O) and methane (CH4) emissions. Hence, we conducted a field trial to measure N2O and CH4 emissions using static chamber–gas chromatograph. Four treatments were used: control (CK) with no fertilizer, 100% chemical N fertilization (CN), the conventional 30% chicken manure N plus 70%CN (CMN + CN), and 30% chicken manure biochar N plus 70%CN (CMBN + CN). The annual cumulative N2O emissions reached 12.4, 63.5, 111.8, and 44.1 kg N2O-N ha−1 for the CK, CN, CMN + CN, and CMBN + CN treatments, respectively. Compared to the CN and CMN + CN treatments, the CMBN + CN treatment reduced N2O emissions by 35.9%–65.7%, while it simultaneously increased the total vegetable yield by 16.1% compared to the CN treatment. Seven seasons mean N2O emission factors are 1.3% for CN, 3.8% for CMN + CN, and 0.9% for CMBN + CN. The CH4 emission was negligible, ranging from 0.07 kg CH4-C ha−1 for the CK treatment to 0.8 kg CH4-C ha−1 for the CN treatment. N2O emissions peaked under the conditions of an interior chamber temperature of around 31.9 °C and the water-filled pore space (WFPS) of the soil being approximately 60%. Future climate change will intensify, triggering higher N2O emissions from subtropical vegetable fields. CMB can be one of the best substitutes for direct chicken manure application as a soil supplement because it has a beneficial effect on improving vegetable yield and reducing N2O emissions in Subtropical China.

Sustainable alternative to irrigated maize monoculture in a maize-dominated cropped area: Lessons learned from a system experiment

Maize is the most-produced food crop in the world and is grown in intensive rotations or in monoculture (continuous maize) systems. As maize production has expanded massively across the world, many concerns have emerged about its local environmental and other global impacts. Agronomists have designed innovative cropping systems and assessed them using system experiments to make arable systems more sustainable. However, knowledge is still lacking on the sustainability of innovative cropping systems compared to highly intensive systems such as irrigated maize-based monoculture. Here, we present the assessment results of a nine-year system experiment in Alsace, France, developed to compare an innovative system based on a diversified rotation and innovative management practices (three-year rotation of maize/soybean/winter wheat (plus a cover crop) combined with reduced tillage) with a continuous maize reference system. The results cover a six-year assessment period following an initial three-year design period. Classic criteria, such as profitability, workload, pesticide use, fossil energy consumption and nitrate leaching, were assessed along with other less studied criteria, such as pesticide leaching risk, soil structure, soil chemical quality and soil biological activity. Sustainability – which includes environmental, social and economic dimensions – was assessed with the MASC 2.0 method. Overall sustainability was substantially enhanced in the innovative system (5 out of 7 sustainability classes) in comparison with the low level of the reference system (2 out of 7). This was due to a clear improvement in the environmental performance (from 2 out of 5 to 5 out of 5) while social performance was high in both systems (4 out of 5) and economic performance was low (2 out of 5) due to very low contribution to economic development. Nevertheless, the innovative system had a major drawback: lower profitability, especially when scenarios included high maize prices. Furthermore, herbicide use on maize was higher in the innovative system than in the reference one. Avenues for progress, such as encouraging stakeholder participation at the assessment stage or additional innovations such as multiple cropping, are suggested.

Evaluation of Pyrazinamide and Pyrazinoic Acid Analogues for Control of Key Weeds in Multiple Crops

Evaluation of Pyrazinamide and Pyrazinoic Acid Analogues for Control of Key Weeds in Multiple Crops

Low-cost Mobile Solar Operated Lift Irrigation System : A Case Study

Effective and judicious use of irrigation water contributes a lot for the management of crop growth and increase in productivity. In the light of increasing demand for irrigation in the state of Assam(India) and to cover the non irrigated area as well as to continue the supplies for the irrigated command area, it becomes imperative to look for a holistic and people centric Low Cost Innovative Irrigation technique. Irrigation water can be assured at every crop field provided we set our mind and put concerted efforts to address it. This paper highlights the Irrigation scenario in Assam with a case study on Low Cost Solar Operated Mobile Lift Irrigation in Assam, for its continuance and contribution towards growth in Agricultural Productivity. This innovation in Irrigation Sector can cause Social transformation by bringing in the development of Agriculture and other allied Sectors. An attempt was also made to establish the economic and operational benefits of the system by making a comparison amongst the different lift Irrigation Schemes in the State. The study advocates for utilization of the non conventional solar energy for irrigating the multiple crops by lifting the surface water sources in the State of Assam by using the Low Cost Solar Operated Mobile Surface Lift Irrigation System. The paper also presents the financial analysis and Key Performance Indicators of the System with a highlight on its diversified application for disaster preparedness and mitigation on the part of Stakeholder Departments with a primary aim to increase Irrigated agriculture productivity

Dissecting the role of salicylic acid in mediating stress response in mungbean cultivars concurrently exposed to Macrophomina phaseolina infection and drought stress

The combined stress studies provide fundamental knowledge that could assist in producing multiple stress resilient crops. The fungal phytopathogen, Macrophomina phaseolina is a major limiting factor in the productivity of the crop, Vigna radiata (mungbean). This fungal species tends to flourish under hot and dry conditions. Therefore, in this study the salicylic acid (SA) mediated stress responses in contrasting mungbean cultivars (Shikha and RMG-975) exposed to combined M. phaseolina infection (F) and drought stress (D) have been elucidated. The combined stress was applied to ten days seedlings in three orders i.e. drought followed by fungal infection (DF), drought followed by fungal infection with extended water deficit (DFD) and fungal infection followed by drought stress (FD). The severity of infection was analyzed using ImageJ analysis. Besides, the concentration of SA has been correlated with the phenylpropanoid pathway products, expression of pathogenesis-related proteins (β-1,3-glucanase and chitinase) and the specific activity of certain related enzymes (phenylalanine ammonia lyase, lipoxygenase and glutathione-S-transferase). The data revealed that the cultivar RMG-975 was relatively more tolerant than Shikha under individual stresses. However, the former became more susceptible to the infection under DFD treatment while the latter showed tolerance. Otherwise, the crown rot severity was reduced in both the cultivars under other combined treatments. The stress response analysis suggested that enhanced chitinase expression is vital for tolerance against both, the pathogen and drought stress. Also, it was noted that plants treat each stress combination differently and the role of SA was more prominently visible under individual stress conditions.

Time Series Field Estimation of Rice Canopy Height Using an Unmanned Aerial Vehicle-Based RGB/Multispectral Platform

Crop plant height is a critical parameter for assessing crop physiological properties, such as above-ground biomass and grain yield and crop health. Current dominant plant height estimation methods are based on digital surface model (DSM) and vegetation indexes (VIs). However, DSM-based methods usually estimate plant height by growth stages, which would result in some discontinuity between growth stages due to different fitting curves. Additionally, there has been limited research on the application of VI-based plant height estimation for multiple crop species. Thus, this study investigated the validity and challenges associated with these methods for estimating canopy heights of multi-variety rice throughout the entire growing season. A total of 474 rice varieties were cultivated in a single season, and RGB images including red, green, and blue bands, DSMs, multispectral images including near infrared and red edge bands, and manually measured plant heights were collected in 2022. DSMs and 26 commonly used VIs were employed to estimate rice canopy heights during the growing season. The plant height estimation using DSMs was performed using different quantiles (50th, 75th, and 95th), while two-stage linear regression (TLR) models based on each VI were developed. The DSM-based method at the 95th quantile showed high accuracy, with an R2 value of 0.94 and an RMSE value of 0.06 m. However, the plant height estimation at the early growth stage showed lower effectiveness, with an R2 < 0. For the VIs, height estimation with MTCI yielded the best results, with an R2 of 0.704. The first stage of the TLR model (maximum R2 = 0.664) was significantly better than the second stage (maximum R2 = 0.133), which indicated that the VIs were more suitable for estimating canopy height at the early growth stage. By grouping the 474 varieties into 15 clusters, the R2 values of the VI-based TLR models exhibited inconsistencies across clusters (maximum R2 = 0.984; minimum R2 = 0.042), which meant that the VIs were suitable for estimating canopy height in the cultivation of similar or specific rice varieties. However, the DSM-based method showed little difference in performance among the varieties, which meant that the DSM-based method was suitable for multi-variety rice breeding. But for specific clusters, the VI-based methods were better than the DSM-based methods for plant height estimation. In conclusion, the DSM-based method at the 95th quantile was suitable for plant height estimation in the multi-variety rice breeding process, and we recommend using DSMs for plant height estimation after 26 DAT. Furthermore, the MTCI-based TLR model was suitable for plant height estimation in monoculture planting or as a correction for DSM-based plant height estimation in the pre-growth period of rice.

Dynamic Energy Use Efficiency, Carbon Input, and Agricultural Benefits of Multiple Cropping in Southern China—A Case Study from Guangdong Province

Background: With the purpose of exploring the development of new quality productive forces in Guangdong, the present study hypothesized that reducing energy and carbon inputs was beneficial for increasing Guangdong’s multi-cropping agricultural energy output and economic returns. Methods: The energy use efficiency of crop production and the corresponding carbon input and agricultural benefit trends from 2011 to 2021 were examined by linear regression analysis for Guangdong Province, China. The corresponding development trends were also predicted using a grey model. Results: The results indicated that the total energy output increased by 12.50%, wherein the energy productivity levels of peanuts, vegetables, mulberry, and fruits increased greatly (51.27–106.17%), while the total energy input and the total carbon input decreased by 12.17% and 6.37%, respectively. Moreover, the energy input per carbon input decreased by 6.19%, while the energy output per carbon input increased by 20.15%. Both energy-related indicators and economic-related indicators all had substantially increased (28.08–44.97% and 83.86–120.91%, respectively). Grey model predictions show that the agricultural output value increased steadily under the current agricultural policy of reducing fossil energy input. Conclusions: The current low-carbon and high-output agricultural model is beneficial for increasing Guangdong’s multi-cropping agricultural economic returns and mitigating greenhouse effects.

Intercropping Industrial Hemp and Cowpea Enhances the Yield of Squash—A Pollinator-Dependent Crop

Cultural crop-production practices are not only engineered to minimize pest incidence but also improve resource use efficiency and increase the diversity of habitat for beneficial insects that provide pollination services. With the increasing cultivation of industrial hemp and the benefits associated with the cultivation of multiple crops, its integration into a polyculture cropping system remains to be evaluated. We intercropped two pollinator-attractive crops, hemp and cowpea, with squash, a pollinator-dependent crop, to evaluate the impact of pollinator abundance and diversity on crop yield. Intercropping significantly increased the overall abundance of pollinators with 79.1% recorded from the intercropping systems compared to 21.9% in the monocropping systems. Sweat bees and bumble bees were the most abundant bees, and Squash+Cowpea was the most diverse cropping system. Intercropping significantly increased the yield of squash with higher squash yield (155%) in Hemp+Squash and (161%) in Squash+Cowpea than in squash monocrop. Also, intercropping resulted in higher hemp yield (64%) in Hemp+Cowpea and (165%) in Hemp+Squash compared to hemp monocrop. This study demonstrated that agricultural systems such as intercropping that are designed to attract pollinators are much more productive by not only improving crop yield but also growers’ returns on investments.

<i>In vitro</i> biocontrol of phytopathogenic fungi isolated from the rhizosphere of multiple crops by a native <i>Trichoderma</i> strain

<i>In vitro</i> biocontrol of phytopathogenic fungi isolated from the rhizosphere of multiple crops by a native <i>Trichoderma</i> strain

Investigating crop performance on urban green roofs using hyperspectral data

This study explores the dynamic relationship between crop plant performance and variety of treatment effects (water levels, diversity, and Sedum) on extensive urban green roofs. Green roofs have gained recognition as a sustainable urban design strategy, offering benefits such as stormwater management, energy efficient, and improved aesthetic enhancements. However, environmental stressors can challenge plant growth and performance on these emerging extensive green roofs. To help cope with these stressors, certain planting techniques have been implemented on green roofs such as plants grown with Sedum and increasing diversity types. However, monitoring the effects of these treatments in a rapid, timely manner are still in its infancy. To monitor plant health (specifically bush beans (Phaseolus vulgaris)) on green roofs, this study utilizes hyperspectral remote sensing technology using two crucial optical parameters: red edge point (REP) and red well point (RWP) to offer new valuable insights into monitoring plant health on green roofs. The results found that both REP and RWP information can detect significant differences between the treatment effects of water treatment (high and low) (p = 0.006, p = 0.001) and plants with or without existence of Sedum (Crassulaceae) (p = 0.01, p = 0.07) but could not find significant difference in diversity effects (single crop or multiple crops) (p = 0.20, p = 0.45). The results of REP and RWP was also able to find that plants with Sedum under low watering treatments showed worse plant performance than plants without Sedum under low watering treatments (p = 0.006, p = 0.006). This provides insights that remote sensing technology can detect that there may have been a competition of resources under low watering treatments and that that REP and RWP has the potential for a future sophisticated green roof monitoring platform.

“A bloodless social revolution”: Land reform and multiple cropping in Cold War Taiwan, 1950–1979

Societal Impact StatementMultiple cropping, the cultivation of several crops on the same land in a year, occupied an important part of Taiwan's agricultural research from 1950 to 1970. This research originated in the context of Taiwan's land reform and diversification programs and their connections to the government's political ambition to maximize food production. The study of how multiple cropping was politicized and depoliticized by different actors helps to expand the narratives of the Green Revolution in Asia, analyze their legacies, and highlight Taiwan's role in the international exchange of visions of agricultural development during the Cold War.Summary Scholars have recently expanded the history of the Green Revolution to move beyond the narrative of North–South technological diffusion. This article enriches the scholarship with the case of multiple cropping in Taiwan and its connection to Cold War geopolitics. Rice productivity in postwar Taiwan was boosted through a land reform launched by the Sino‐American Joint Commission on Rural Reconstruction (JCRR) in the 1950s. Backed by American aid and staffed by scientists from the Republic of China (ROC) government, the JCRR envisioned to turn tenant farmers into landowners so as to encourage labor input and adoption of seeds and fertilizers. By 1960, the JCRR presented its reform as a “bloodless social revolution” and extended its focus to multiple cropping through a diversification program. The JCRR further created the Asian Vegetable Research and Development Center (AVRDC) in 1971 to spread Taiwan's breeding and cropping techniques. The ROC's diplomatic isolation in the 1970s, however, prompted the center to reinterpret Taiwan's success in multiple cropping from a political achievement to a technological triumph, thus reinforcing the technology‐driven narrative used by the International Rice Research Institute (IRRI). Through Taiwan's influences on IRRI's rice breeding and multiple cropping research, this paper illustrates that the history of the Green Revolution requires more complex narratives. In addition, with Taiwan's political and economic transition since the 1980s, farmers began to reclaim their voice and influence agricultural policies. The case thus highlights the need of democratic participation in agricultural research, a concern that remains relevant today.

Pseudomonas hefeiensis sp. nov., isolated from the rhizosphere of multiple cash crops in China.

Three bacterial strains, FP250T, FP821, and FP53, were isolated from the rhizosphere soil of oilseed rape, licorice, and habanero pepper in Anhui Province, Xinjiang Uygur Autonomous Region, and Jiangsu Province, PR China, respectively. All strains were shown to grow at 4-37 °C and pH 6.0-9.0, and in the presence of 0-4.0 % (w/v) NaCl. Phylogenetic analyses based on 16S rRNA gene sequences or housekeeping genes (16S rRNA, gyrB, rpoB, and rpoD) and phylogenomic analysis showed that strains FP250T, FP821, and FP53 belong to the genus Pseudomonas, and are closely related to Pseudomonas kilonensis DSM 13647T, Pseudomonas brassicacearum JCM 11938T, Pseudomonas viciae 11K1T, and Pseudomonas thivervalensis DSM 13194T. The DNA G+C content of strain FP205T was 59.8 mol%. The average nucleotide identity and digital DNA-DNA hybridization values of strain FP205T with the most closely related strain were 93.2 % and 51.4 %, respectively, which is well below the threshold for species differentiation. Strain FP205T contained summed feature 3 (C16 : 1 ω6c and/or C16 : 1 ω7c), summed feature 8 (C18 : 1 ω7c and/or C18 : 1 ω6c) as major fatty acids, and diphosphatidylglycerol along with phosphatidylethanolamine and aminophospholipid as major polar lipids. The predominant isoprenoid quinone was ubiquinone-9. Based on these phenotypic, phylogenetic, and chemotaxonomic results, strain FP205T represents a novel species of the genus Pseudomonas, for which the name Pseudomonas hefeiensis sp. nov. is proposed. The type strain is FP205T (=ACCC 62447T=JCM 35687T).

MPSARB: design of an efficient multiple crop pattern prediction system with secure agriculture-record-storage model via reconfigurable blockchains

MPSARB: design of an efficient multiple crop pattern prediction system with secure agriculture-record-storage model via reconfigurable blockchains

Spatial autocorrelation and driving factors of carbon emission density of crop production in China.

Mitigating carbon emissions from crop production is essential for addressing global warming. At a macro-level, existing studies have often relied on the calculation of carbon emission intensity of crop production to understand comparable carbon effects between regions. However, this approach obscures the differences in crop planting scale and natural attributes across regions, leaving room for improvement in the methods and scope of analysis. To extend the existing research, we proposed an idea for calculating the carbon emission density of crop production based on planting area. Additionally, we developed an analytical framework for driving factors of carbon emission density of crop production from a spatial interaction perspective. The provincial carbon emission density of crop production in mainland China between 2000 and 2020 was calculated, and spatial econometric models were utilized to investigate the spatial autocorrelation and driving factors. The results indicate that the national average carbon emission density of crop production was 1.462 t/hm2 annually. Over 21years, the carbon emission density of agricultural materials, rice cultivation, soil management, and straw burning evolved from 0.384 to 0.470 t/hm2, 0.409 to 0.367 t/hm2, 0.171 to 0.169 t/hm2, and 0.317 to 0.448 t/hm2, respectively. The global Moran's index indicated a positive spatial autocorrelation of carbon emission density of crop production and the subdivided carbon sources among provinces. Regarding direct effects, an increase in the proportion of paddy fields in cropland composition and irrigation efficiency would significantly promote the carbon emission density, while factors such as cropland area, multiple cropping, agricultural personnel numbers, departmental proportion, and disaster degree would decrease the local carbon emission density. Certain factors, such as cropland area and agricultural disasters, had a spatial spillover effect on carbon emission density between provinces. The study suggests harnessing key drivers and spatial spillover effects to achieve regional low-carbon crop production.

Green manure removal with reduced nitrogen improves saline-alkali soil organic carbon storage in a wheat-green manure cropping system

The incorporation of green manure into cropping systems is a potential strategy for sequestering soil carbon (C), especially in saline-alkali soil. Yet, there are still unknown about the substitution impacts of green manure on nitrogen (N) fertilizer in wheat-green manure multiple cropping system. Herein, a five-year field experiment was performed to determine the impact of three levels of N fertilizer inputs [i.e., N fertilizer reduced by 0 % (100N), 10 % (90 N), and 20 % (80 N)] with aboveground biomass of green manure removal (0GM) and return (100GM) on soil organic carbon (SOC) storage and its primary determinants. The results demonstrated that no significant interaction on SOC storage was detected between green manure and N fertilizer management. 80 N enhanced SOC storage in bulk soil by 7.4 and 13.2 % in 0–20 cm soil depth relative to 100 N and 90 N (p < 0.05). Regardless of N fertilizer levels, compared with 100GM, 0GM increased SOC storage in bulk soil by 14.2–34.6 % in 0–40 cm soil depth (p < 0.05). This was explained by an increase in soil macro-aggregates (>2 and 0.25–2 mm) proportion contributing to SOC physical protection. Meanwhile, the improvement of SOC storage under 0GM was due to the decrease of soil C- and N-acquisition enzyme activities, and microbial resource limitation. Alternatively, the variation partitioning analyses (VPA) results further suggested that C- and N-acquisition enzyme activities, as well as microbial resource limitation were the most important factors for SOC storage. The findings highlighted those biological factors played a dominant role in SOC accumulation compared to physical factors. The aboveground biomass of green manure removal with N fertilizer reduced by 20 % is a viable option to enhance SOC storage in a wheat-green manure multiple cropping system.

System shift in rice: Processes and pathways of change in rice-based production systems of Southeast Asia

CONTEXTPredicting future production trends and associated land use and management practices requires an understanding of past changes in productivity and of pathways of evolving system configurations. We argue that rice systems' evolution reflects a process of adaptation to changing availabilities of production resources and the adoption of technological innovations and that differs by marginality/favorability of sites. Understanding past change trends and their determinants can help avoiding undesirable future developments and guide policy decisions for a sustained supply of rice. OBJECTIVEWe aimed to assess agronomic system change and practices, to quantify pathways of change and to identify likely drivers of but also possible risks or opportunities associated with observed patterns of agronomic system transformation in six representative lowland rice production environments in Asia. METHODSWe implemented a diachronic analysis (years 2000 vs. 2018) of rice production practices and yield attributes in 1024 households. We documented changes between 2000 and 2018 in lowland rice-based systems in six rice-growing environments in the Philippines, Myanmar and Cambodia, differentiating marginal and favorable sites in irrigated and in rainfed environments. RESULTS AND CONCLUSIONFarmers' household attributes, resource endowment, rice yields, and key constraints differed among sites. We observed relatively low annual yield in marginal (2.2–3.0 t/ ha) than favorable (3.3–8.9 t/ ha) sites depending on countries and seasons. The farmers adopted intensification related agronomic practices has increased significantly between 2000 and 2018, especially in dry season (i.e., improved seeds by 28%, mechanical tillage by 52%, direct seeding by 21%, combined harvester by 62%). The marginality of climatic and edaphic conditions, the systems' evolutionary state in 2000, and differential pressures (policy environment), opportunities (technological change) and household attributes (resource endowment) determined the observed transition pathways across study sites. SIGNIFICANCEThe trends towards maximizing land use intensity (double or multiple cropping), converging in the emergence of high-input and highly mechanized (laborsaving) in irrigated, and diversified rotations in rainfed rice production systems may help to elucidate agricultural research needs and potentially predict the requirements for future sustainable intensification of rice-based systems. Additionally, we argue for a continued need for further mechanization of rice establishment, especially shifting from transplanting to direct seeding during dry and wet seasons, and of the rice harvest, especially during wet season under fully irrigated environments.

Boosting crop classification by hierarchically fusing satellite, rotational, and contextual data

Accurate early-season crop type classification is crucial for the crop production estimation and monitoring of agricultural parcels. However, the complexity of the plant growth patterns and their spatio-temporal variability present significant challenges. While current deep learning-based methods show promise in crop type classification from single- and multi-modal time series, most existing methods rely on a single modality, such as satellite optical remote sensing data or crop rotation patterns. We propose a novel approach to fuse multimodal information into a model for improved accuracy and robustness across multiple crop seasons and countries. The approach relies on three modalities used: remote sensing time series from Sentinel-2 and Landsat 8 observations, parcel crop rotation and local crop distribution. To evaluate our approach, we release a new annotated dataset of 7.4 million agricultural parcels in France (FR) and the Netherlands (NL). We associate each parcel with time-series of surface reflectance (Red and NIR) and biophysical variables (LAI, FAPAR). Additionally, we propose a new approach to automatically aggregate crop types into a hierarchical class structure for meaningful model evaluation and a novel data-augmentation technique for early-season classification. Performance of the multimodal approach was assessed at different aggregation levels in the semantic domain, yielding to various ranges of the number of classes spanning from 151 to 8 crop types or groups. It resulted in accuracy ranging from 91% to 95% for the NL dataset and from 85% to 89% for the FR dataset. Pre-training on a dataset improves transferability between countries, allowing for cross- domain and label prediction, and robustness of the performances in a few-shot setting from FR to NL, i.e., when the domain changes as per with significantly new labels. Our proposed approach outperforms comparable methods by enabling deep learning methods to use the often overlooked spatio-temporal context of parcels, resulting in increased precision and generalization capacity.

Strip tillage promotes crop yield in comparison with no tillage based on a meta-analysis

Conservation tillage (e.g. no tillage, minimum tillage) is regarded as an effective way to maintain sustainable crop productivity and improve soil quality globally. However, the claim that conservation tillage could improve crop yield are still controversial. It is hypothesized that whether conservation tillage increase crop yield in comparison with conventional tillage (CT) depends on the different conservation tillage practices, for example, no tillage (NT) and strip tillage (ST), and different variables including in agronomic managements, climate conditions, and soil properties. Herein, a meta-analysis was conducted to evaluate how tillage practices affect crop yield and which factors dominate yield performance mostly. Based on the 53 published articles with 290 paired-comparisons across the world, the effects of ST vs. CT and ST vs. NT on crop yield were conducted. It was showed that crop yield under ST had an increasing trend compared to that under CT and NT. Especially, ST significantly increased crop yield by 4.81% in contrast with NT, which indicated that ST might be a promising practice of conservation tillage in terms of crop yield. Under the agronomic managements of continuous cropping, multiple cropping, graminaceous crops, and straw removing, ST significantly increased crop yields by 5.40%, 10.29%, 7.66%, and 7.60% compared to NT, respectively. ST achieved significantly higher crop yield by 5.68% on average and 11.63% as compared to NT under all soil texture and neutral soil. Concerning the climate conditions, crop yield significantly increased by 3.64% under ST as compared to NT in cooler area where mean annual temperature (MAT) was lower than 10°C. Importance analysis indicated that cropping system and MAT were the key factors affecting the performance of tillage practice on crop yield. Overall, present study revealed that ST might be a favorable conservation tillage practice in continuous and multiple cropping systems with graminaceous crop (e.g. maize) in cooler (MAT <10℃) region in terms of yield promotion. This meta-analysis study demonstrated the importance of conservation tillage optimization for food safety and sustainable development of agriculture.