Agronomic Research Research Articles

An update on the nutritional profiles of quinoa (Chenopodium quinoa Willd.), amaranth (Amaranthus spp.), and chia (Salvia hispanica L.), three key species with the potential to contribute to food security worldwide

AbstractOne of the major challenges facing the world nowadays is to ensure enough access to healthy food for a growing population. Under this food scenario, it should be noted that increasing food production is as important as improving its nutritional quality. Thus, different agronomy research and innovation programs have pursued food security through the increase in the quantity and nutritional quality of plant‐based foods. One key aspect in this respect is to increase agrobiodiversity by expanding the cultivation of underutilized highly nutritious crops such as chia, quinoa, or amaranth. The outstanding nutritional value of these crops resides in the compositional characteristics of their seeds, which include the presence of significant levels (and a good balance) of proteins, essential amino acids, lipids, and other components such as phenols, minerals, fiber, or vitamins, all contributing to support nutritious diets that also has health benefits such as the prevention of cardiovascular diseases. All of them, chia, amaranth, and quinoa, are considered emerging crops outside their center of origin (which is mainly located in South America), and their cultivation has been expanded worldwide in the last decade. This review mainly highlights recent knowledge about the nutritional characteristics of these three Latin American crops, with the aim of providing an updated information regarding the compositional profiles of their seeds.

Energy Dynamics of Rice Production in Eastern India as Influenced by Resource Conserving Establishment Methods and Weed Management

The field experiment was conducted during the wet seasons of 2020 and 2021, at the Agronomy Research Farm of Odisha University of Agriculture and Technology, Bhubaneswar, Odisha, India to assess the input energy requirements and output energy production of establishment methods and weed management in rice. The treatments included three establishment methods viz., Dry-direct seeded rice (Dry-DSR), Wet-DSR and puddled transplanted rice (PTR) in main plot and six weed management treatments viz., hand weeding, oxadiargyl @ 90 g ha-1 as pre-emergence (PE) followed by (fb.) penoxsulam+cyhalofop @ 135 g ha-1 as post-emergence (PoE), oxadiargyl @ 90 g ha-1 (PE) fb. triafamone+ethoxysulfuron @ 60 g ha-1 (PoE), oxadiargyl @ 90 g ha-1 (PE) fb. bispyribac sodium @ 25 g ha-1+fenoxaprop @ 56 g ha-1 (PoE), brown manuring (DSR) / green manuring (PTR) fb. 2,4-D at 25 DAS/T and unweeded control in subplot. Dry-DSR utilised 3.2% less input energy than Wet-DSR. PTR recorded highest energy use efficiency (11.88), energy efficiency ratio (5.78), energy productivity (0.393 kg MJ-1) and energy profitability (10.88), followed by Dry-DSR and Wet-DSR. The highest specific energy (4.59 MJ kg-1) was estimated in Dry-DSR, differing significantly with other establishment techniques. Among weed management options, the highest energy use efficiency (11.89) and energy profitability (10.89) was recorded with application of oxadiargyl (PE) fb. penoxsulam+cyhalofop (PoE), being at par with hand weeding, oxadiargyl (PE) fb. bispyribac sodium+fenoxaprop (PoE). Oxadiargyl fb. penoxsulam+cyhalofop under Dry-DSR was highly economic energy efficient, but at par with oxadiargyl fb. bispyribac+fenoxaprop under the same establishment technique.

Growth and Yield of Finger Millet as Influenced by Tillage and Organic Nutrient Management under Finger Millet-french Bean Cropping System

A field experiment on ‘Growth and yield of finger millet as influenced by tillage and organic nutrient management under finger millet-french bean cropping system’ was conducted at Agronomical Research Farm, Birsa Agricultural University, Kanke, Ranchi, Jharkhand during 2020-21 and 2021-22. The experiment laid out in a split-plot design with three replication. The experiment consisted of four main plot treatments viz., conventional tillage–conventional tillage (CT–CT), conventional tillage–zero tillage (CT–ZT), zero tillage–conventional tillage (ZT–CT) and zero tillage–zero tillage (ZT-ZT) and subplot has four treatments with different sources of organic nutrient management viz., 100% N through FYM, 100% N through vermicompost, 50% N through FYM + 50% N through vermicompost and 75% N through FYM + 25% N through vermicompost. Significantly highest value of number of tillers (121.15), leaf area index at 90 DAS (2.65), dry matter accumulation at maturity (865.61 g/m2), crop growth rate at 90 DAS-maturity (9.47 g/m2/day), number of effective tillers (112.96), number of fingers/ear (6.66), number of grains/ear (1085.26), ear weight (6.59 g), grain (23.90 q/ha) and straw yield (38.85 q/ha) were observed in conventional tillage- conventional tillage. Among organic source, 100% N through vermicompost gave significant maximum value of number of tillers (121.37), leaf area index at 90 DAS (2.67), dry matter accumulation at maturity (873.36 g/m2), crop growth rate at 90 DAS-maturity (9.67 g/m2/day), number of effective tillers (113.12), number of fingers/ear (6.76), number of grains/ear (1094.19), ear weight (6.61 g), grain (24.25 q/ha) and straw yield (38.93 q/ha).

Leaf Color Chart (LCC)-Based Precision Nitrogen Management for Assessing Phenology, Agrometeorological Indices and Sustainable Yield of Hybrid Maize Genotypes under Temperate Climate

Excessive nitrogenous fertilization in years resulted in larger nitrogen and profit losses. This problem can be reduced by using need-based and time-specific nitrogen management. Therefore, a field experiment was carried out during the Kharif season of 2019 and 2020 in order to evaluate the impact of precision nitrogen management on the phenology, yield and agrometeorological indices of hybrid maize genotypes at the Agronomy Research Farm, FoA Wadura, Sopore, SKUAST-Kashmir. The experiment was carried out in split-plot design consisting of maize hybrids (Shalimar Maize Hybrid-2 Vivek-45 and Kanchan-517) as main plot treatments and precision nitrogen management (T1: Control, T2: Recommended N, T3: 25% N as basal ≤ LCC 3@20 kg N ha−1, T4: 25% N as basal ≤ LCC 3@30 kg N ha−1, T5: 25% N as basal ≤ LCC 4@20 kg N ha−1, T6: 25% N as basal ≤ LCC 4@30 kg N ha−1, T7: 25% N as basal ≤ LCC 5@20 kg N ha−1 and T8: 25% N as basal ≤ LCC 5@30 kg N ha−1) as sub-plot treatments. Results demonstrated that maize hybrids showed a non-significant difference in attaining different phenophases during both years. However, Shalimar Maize Hybrid-2 demonstrated higher grain (62.35 and 60.65 q ha−1) and biological yield (170.26 and 165.86 q ha−1), a higher number of days to attain different phenological stages in comparison to Vivek-45 and Kanchan-517 thereby achieved higher heat units, PTUs, HTUs, PTI. The application of nitrogen through LCC ≤ 5@30 kg N ha−1 noted higher grain yield (61.27 and 59.13 q ha−1) and biological yield (171.30 and 166.13 q ha−1) during 2019 and 2020 respectively. Higher values of Growing degree days (GDD), Heliothermal units (HTU), Photothermal units (PTU), Phenothermal index (PTI), heat use efficiency (HUE) and radiation use efficiency (RUE) were observed in the application of nitrogen through LCC ≤ 5@30 kg N ha−1 and required the highest number of days to reach different phenophases than other treatments during crop growing seasons of 2019 and 2020. The results demonstrated that Nitrogen application based on LCC ≤ 5@30 proved effective and should be adopted in maize hybrids especially in Shalimar Maize Hybrid-2 to attain higher yield under the temperate climate of Kashmir Valley.

Intercropping Spinach and Red Amaranth With Brinjal Under Different Planting System

The experiment was conducted at Agronomy Research Field of Bangladesh Agricultural Research Institute, Gazipur, during the rabi season of 2018 to 2019 and 2019 to 2020 to find out the suitable crop combination of spinach (Spinacia oleracea) and red amaranth (Amaranthus cruentus) with brinjal (Solanum melongena) for higher brinjal equivalent yield, monetary advantage and maximize land utilization through intercropping system. Treatments were: T1 = 2 rows spinach (50%) in between two rows of brinjal (100%), T2 = 3 rows Spinach (75%) in between two rows of brinjal (100%), T3 = 2 rows red amaranth (50%) in between two rows of brinjal (100%), T4 = 3 rows red amaranth (75%) in between two rows of brinjal (100%), T5 = Sole brinjal ( 80 cm × 60 cm), T6 = Sole spinach (Line to line 20 cm) and T7 = Sole red amaranth (Line to line 20 cm) were used in the study. All the intercropping combinations showed better performance in terms of brinjal equivalent yield, gross return and benefit cost ratio (BCR) over sole crops. Among the intercropping combinations, 3 row spinach (75%) in between two rows of brinjal (100%) was the most feasible and profitable intercropping system in respect of brinjal equivalent yield (34.72 t ha-1), land equivalent ratio (1.57), gross return (Tk. 6,94,346 ha- 1), gross margin (Tk. 4,59,088 ha-1) and benefit cost ratio (2.95). From the two years, results revealed that all intercropping treatments were productive as compared to sole treatments but 3 rows spinach (line to line 20 cm) 75% in between two rows of brinjal (80 cm × 60 cm) 100% intercropped combination might be agronomically feasible and economically profitable.
 Bangladesh Agron. J. 2022, 25(1): 91-96

Date of Planting, Spacing and Integrated Nutrient Management Practices Improves Soil Microbial Populations and Soil Fertility Status Under Rice -Arhar Cropping System in Acidic Soils of Eastern India

ABSTRACT Rice (Oryza sativa L.) is a nutrient-exhausting crop, sustainable productivity of rice based cropping system can be achieved through appropriate nutrient management and crop diversification through incorporation of pulse into this system. Considering the above facts, a field experiment on rice-arhar system was conducted for two consecutive years (2018 and 2019) during kharif seasons at the Agronomy research Farm of Odisha University of Agriculture and Technology, Bhubaneswar having sub-humid climate with two date of planting, three nutrient management and three row spacing. Soil physico-chemical properties like N, soil organic carbon (SOC) was found higher with earlier planting, soil-test-based fertilizer Recommendation (STBFR) + Farmyard Manure (FYM) in rice and 30 cm row spacing in arhar. The system nutrient uptake of 219.76 kg N ha−1, 38.25 kg P ha−1 and 197.29 kg K ha−1 and microbial activities in terms of dehydrogenase activity (DHA) (241.9 mg TPF g−1 soil 24 hr−1), alkaline phosphatase activity (APA) (376.7 mg p-nitrophenol kg−1 soil 1 h−1), microbial biomass Carbon (MBC) (260.3 μg g−1 of dry soil), microbial biomass nitrogen (MBN) (93.7 μg N g−1 soil) was registered with earlier planting, STBFR + FYM in rice and 30 cm row spacing in arhar. Higher positive N and K balance over initial (actual balance) in rice-arhar cropping system was observed in the treatment fertilized with both organic and inorganic sources of nutrients.

An Open Soil Health Assessment Framework Facilitating Sustainable Soil Management.

The crucial role of healthy soil in achieving sustainable food production and environment is increasingly recognized, as is the importance of proper assessment of soil quality. We introduce a new framework, open soil index (OSI), which integrally evaluates soil health of agricultural fields and provides recommendation for farming practices. The OSI is an open-source modular framework in which soil properties, functions, indicators and scores, and management advice are linked hierarchically. Soil health is evaluated with respect to sustainable crop production but can be extended to other ecosystem functions. The OSI leverages the existing knowledge base of agronomic research and routine laboratory data, enabling its application with limited cost. The OSI is a generic framework that can be adopted for specific regions with specific objectives. As a proof of concept, the OSI is implemented for all (>700,000) Dutch agricultural fields and illustrated with 11 pairs ("good" and "poor") of local fields and 32 fields where soil quality and crop yield have been monitored. The OSI produced reasonable evaluation for most pairs when soil physical functions were refined with on-site soil visual assessment. The soil functions are sufficiently independent and yet together reflect complex multidimensionality of soil quality. The framework can facilitate designing sustainable soil management programs by bridging regional targets to field-level actions.

Towards a Discovery of a Zinc-Dependent Phosphate Transport Road in Plants.

Owing to the impending global scarcity of high-quality sources of phosphate (Pi) fertilizers, lowering its use in crop production requires improved insights into factors stimulating Pi uptake from the soil as well as the efficacious use by plants. Following decades of extensive research on plants' adaptation to Pi deficiency with mitigated success in the field, a better understanding of how plants exposed to zinc (Zn) deficiency accumulate much more Pi provides a novel strategy in comparison to when plants are grown in Zn-rich soils. In this context, we review current knowledge and molecular events involved in the Pi and Zn signaling crosstalk in plants that will bear great significance for agronomical and rudimentary research applications.

Evaluation of grain yield performance and its stability in various spring barley accessions under condition of different agroclimatic zones of Ukraine

Two extremely urgent problems of biological and agronomic research nowadays are ensuring an optimal balance between usage of natural resources to meet rapidly growing needs for food production and preservation of biodiversity. It is also important to extend the genetic diversity of the main crop varieties in agroecosystems. At the same time, modern varieties should be characterized by a combination of high yield and preserving yield stability under variable conditions. Solving the outlined tasks requires comprehensive research and involvement in breeding process of the genetical diversity concentrated in genebanks of the world. Barley (Hordeum vulgare L.) is one of the most important crops that satisfy the various needs of humanity. In respect to this, in 2020–2022, a multi-environment trial was conducted in three agroclimatic zones of Ukraine (Forest-Steppe, Polissia, and Northern Steppe). We studied 44 spring barley collection accessions of different ecological and geographical origin, different subspecies and groups of botanical varieties which were obtained from the National Center for Plant Genetic Resources of Ukraine. Statistical indices (Hom, Sc) and graphical models (GGE biplot, AMMI) were used to interpret the yield performance and its stability. Both individual ecological sites in different years and combinations of different sites and years of trials were characterized for productivity, discriminating power and representativeness. The environments differed quite strongly among themselves in terms of these indicators. It was established that most of the genotypes were characterized by higher adaptability to individual environmental conditions (stability in different years), compared to adaptability for all agroclimatic zones (wide adaptation). A strong cross-over genotype by environment interaction was found for most studied accessions. Nevertheless, both genotypes with very high stability in only one agroclimatic zone (Amil (UKR), Gateway (CAN)) and genotypes with a combination of high adaptability to one or two ecological niches and relatively higher wide adaptability (Stymul (UKR), Ly-1064 (UKR), Rannij (KAZ), Shedevr (UKR), and Arthur (CZE)) were identified. There were also the accessions which did not show maximum performance in the individual sites, but had relatively higher wide adaptability (Ly-1059 (UKR), Ly-1120 (UKR), Diantus (UKR), and Danielle (CZE)). In general, the naked barley genotypes were inferior to the covered ones in terms of yield potential and wide adaptability, but at the same time, some of them (CDC ExPlus (CAN), CDC Gainer (CAN), and Roseland (CAN)), accordingly to the statistical indicators, had increased stability in certain ecological sites. Among naked barley accessions relatively better wide adaptability according to the graphical analysis was found in the accession CDC McGwire (CAN), and by the statistical parameters CDC ExPlus (CAN) was better than standard. The peculiarities of yield manifestation and its variability in different spring barley genotypes in the multi-environment trial revealed in this study will contribute to the complementation and deepening of existing data in terms of the genotype by environment interaction. Our results can be used in further studies for developing spring barley variety models both with specific and wide adaptation under conditions of different agroclimatic zones of Ukraine. The disitnguished accessions of different origin and botanical affiliation are recommended for creating a new breeding material with the aim of simultaneously increasing yield potential and stability, as well as widening the genetic basis of spring barley varieties.

Aroma and terpenoid profile of Chardonnay clone 809: from berry to sparkling wine

Clone selection is a viticultural practice applied to evaluate the behaviour and agronomic and flavour characteristics of a material in a determined environment to obtain wines with different aromatic attributes. The clones of the cultivar Chardonnay comprise aromatic and non-aromatic clones that can provide different sensorial qualities. This work aimed to evaluate the volatile compounds formed in clone 809 (aromatic) to produce a more aromatic sparkling wine in Serra da Mantiqueira (southeast Brazil) and compare it to clone 76 (non-aromatic) from the berry to the wine. The vineyards are in Caldas (Minas Gerais – Brazil) at the Agronomical Research Centre of Minas Gerais (EPAMIG), and the vinification was performed using the Champenoise method (18 months in sur lie). HS-SPME/GC-MS identified free volatile compounds in two consecutive seasons, 2017 and 2018, in grape, musts, base wines and sparkling wines. The number and abundance of monoterpenoid compounds in clone 809 were statistically significant compared to clone 76 for all sample steps. Multivariate and principal component analyses (PCA) made it possible to differentiate the base and sparkling wines by the clones in both vintages for the second component (16.8 %). Furthermore, the sparkling wines of clone 809 were discriminated for the third component (15.1 %) by the monoterpenes: α-terpineol, linalool, ß-myrcene, hotrienol, nerol oxide, and limonene. The data suggest that Chardonnay clone 809 can contribute to obtaining a sparkling wine with an additional floral and sweet character.

Aphid BCR4 Structure and Activity Uncover a New Defensin Peptide Superfamily.

Aphids (Hemiptera: Aphidoidea) are among the most detrimental insects for agricultural plants, and their management is a great challenge in agronomical research. A new class of proteins, called Bacteriocyte-specific Cysteine-Rich (BCR) peptides, provides an alternative to chemical insecticides for pest control. BCRs were initially identified in the pea aphid Acyrthosiphon pisum. They are small disulfide bond-rich proteins expressed exclusively in aphid bacteriocytes, the insect cells that host intracellular symbiotic bacteria. Here, we show that one of the A. pisum BCRs, BCR4, displays prominent insecticidal activity against the pea aphid, impairing insect survival and nymphal growth, providing evidence for its potential use as a new biopesticide. Our comparative genomics and phylogenetic analyses indicate that BCRs are restricted to the aphid lineage. The 3D structure of BCR4 reveals that this peptide belongs to an as-yet-unknown structural class of peptides and defines a new superfamily of defensins.

Effects of Charcoal Preservation Methods on the Biochemical Parameters of Three Varieties of Plantain (Musa ssp)

Aims: To contribute to solving plantain post-harvest losses, six preservation methods combining charcoal and polyethylene bags were experimented on three different varieties of plantain (SACI, Big-Ebanga, and Orishele).
 Place and Duration of Study: This work was carried out at the Biocatalysis and Bioprocesses Laboratory of Nangui Abrogoua University in Abidjan and the Food Technology Laboratory of the National Center for Agronomic Research in Côte d'Ivoire.
 Methodology: Some Biochemical parameters of these fruits are monitored to know the effects of these preservation methods during storage.
 Results: The outcomes indicate an average shelf green life extension of up to 30 days for fruits preserved in polyethylene containing charcoal, while fruits preserved in polyethylene without charcoal have only 24 days on average. The control test (fruits stored in the open air) showed an average shelf green life of 12 days. During storage, total carbohydrate levels increase and values range from 92.49% to 70.05%. Those of total sugars also increase and the levels evolve from 0.47 to 30.83 g/100 g DM. On the other hand, there is a decrease in starch levels (42.66 and 64.05 mg/100g DM).
 Conclusion: Charcoal can extend the shelf green life of plantain bananas for up to a month. These methods can be recommended to actors in the sector to reduce post-harvest losses.

Unravelling Potential Health-Beneficial Properties of Corema album Phenolic Compounds: A Systematic Review.

Corema (C.) album belongs to the family Ericaceae and can be found in the Iberian Peninsula, especially on the coastal areas facing the Atlantic coast. C. album berries have been used for centuries in traditional medicine. Recent studies have revealed that not only the berries but also the leaves have relevant antioxidant, antiproliferative, and anti-inflammatory properties, bringing this plant to the forefront of discussion. A systematic review of the literature was carried out to summarize the phenolic compounds and bioactive properties identified in C. album berries and leaves and to search for research gaps on this topic. The search was conducted in three electronic databases (PubMed, SCOPUS, and Web of Science) using PRISMA methodology. The inclusion criteria were the chemical compositions of the berries, leaves, or their extracts and their bioactive properties. The exclusion criteria were agronomic and archaeological research. The number of studies concerning phenolic compounds’ composition and the bioactive properties of C. album berries and leaves is still limited (11 articles). However, the variety of polyphenolic compounds identified make it possible to infer new insights into their putative mechanism of action towards the suppression of NF-kB transcription factor activation, the modulation of inflammatory mediators/enzymes, the induction of apoptosis, the modulation of mitogen activated protein kinase, cell cycle arrest, and the reduction of oxidative stress. These factors can be of major relevance concerning the future use of C. album as nutraceuticals, food supplements, or medicines. Nevertheless, more scientific evidence concerning C. album’s bioactivity is required.

3D characterization of crop water use and the rooting system in field agronomic research

Most field crop phenotyping research has focused on the above-ground parts of crops, ignoring a “hidden half”: the rooting system and its activity. Here we propose and test a new approach to produce 3D characterizations of crop water use and root activity in large field genotype (G) by environment (E) by management (M) experimentation, using electromagnetic induction (EMI) instrument coupled with a quasi-2D inversion algorithm, and crop canopy sensing technologies. A root activity factor (R) was calculated as a function of crop water use, soil water availability, and an indicator of crop demand. We ask i) can this approach provide accurate 3D characterizations of sorghum water use and root activity?, and (ii) does the approach capture complex GxExM dynamics?. This study was conducted based on an on-farm field experiment consisting of the factorial combination of six commercial sorghum genotypes (G), three times of sowing, two levels of irrigation (E), four plant densities (M), and three replications. Two EMI surveys ten days apart were collected using a DUALEM-21S sensor. An artificial neural network (ANN) model was developed to predict 3D soil moisture (θv) using depth-specific true soil electrical conductivity (σ, mS m−1) estimated by the inversion algorithm. Crop water use between surveys was described as the difference of θv. A multispectral index derived from satellite imagery was used as a proxy for crop demand i.e., size of the crop canopy. Principal components analysis, linear mixed models, and recursive partitioning tree techniques and crop-eco-physiological principles were used to untangle complex GxExM interactions. Results indicate that 3D crop water use could be predicted with high accuracy (LCCC = 0.81) and low prediction error (RMSE = 0.03 cm3 cm−3). The calculated water use and the value of R were significantly affected by depth, crop growth stage, irrigation treatment, plant density, and their interactions. At flowering, roots were most active at 0–1.3 m under irrigation, and deeper (0.5–1.5 m) under dryland treatment. The highest water use was for three genotypes (i.e., C, E and F) grown under irrigation and high plant densities (i.e., 9 and 12 pl m-2). The smallest water use was observed under dryland treatment, particularly for two genotypes (i.e., B and C) and high plant densities. For the crops at vegetative stages, the values of water use and R were highest in the top 0.5 m of soil depth. Larger water use was observed under dryland treatment and high plant densities, while the effects of genotypes were small (not significant). We conclude that the approach provides a rapid, accurate and cost-efficient option to phenotype crop root activity i.e., water use, in large field experimentation. We also argue that the improved understanding of the crop water use dynamics can help inform optimum combinations of genotypes and management options i.e., crop designs, across contrasting environments, and help untangle complex GxExM interactions.

Towards sustainable productivity enhancement of rice-based farming systems in sub-Saharan Africa

In the past 50 years, rice has become an important crop for food security in sub-Saharan Africa. However, rice yields remain relatively low, and large yield gaps exist. This Special Issue brings together agronomy research on rice-based farming systems in sub-Saharan Africa and addresses three main, overarching questions: (1) what has been achieved in the past decades in terms of rice agronomy in sub-Saharan Africa, (2) what is the state-of-the-art regarding development of technologies and (3) what will be likely or required future directions? The broad topics included in this Special Issue are (1) yield trends and yield gap analyses, (2) soil & nutrient, water, weed and integrated crop management practices, (3) cropping systems, (4) genetic improvements, (5) crop simulation modeling, and (6) assessment of farmers’ rice cultivation practices and the sustainability of these practices. The papers cover different sub-regions, from the Sahel to the highlands of Madagascar and three major rice growing environments (irrigated lowlands, rainfed lowlands, and rainfed uplands). In this paper we describe the major challenges in the rice production sector in sub-Saharan Africa and historical efforts on agronomy research, and we provide a short introduction and discussion on the papers presented in this Special Issue. This Special Issue arrives at six main recommendations. 1. There is a need to increase research and development efforts focusing on rainfed rice-based systems. 2. More attention needs to be paid to research on the farming system or landscape level, aimed at development of integrated cropping and farming systems and integrated agronomic solutions. 3. Current and future agronomic rice research should thematically center around sustainability, including judicious natural resources management, climate change adaptation and mitigation, and conservation of biodiversity and environments. 4. To operationalize this, sustainability performance indicators need to be developed and used. 5. There is broad consensus regarding the need for more labor-saving technologies, including mechanization options, provided these do not increase the ecological footprint of production systems. 6. Future rice agronomy research work should be interdisciplinary and transdisciplinary, to better address the myriad of challenges of smallholder farmers in Africa. Papers presented in this Special Issue should inform on the state-of-the art in rice agronomy in SSA, and on ways to sustainably enhance rice production and self-sufficiency in this region.

Successful approaches for on-farm experimentation

On-farm experiments are used increasingly in agronomic research because they are commercially relevant, but they can carry greater risks of failure than traditional small plot experiments conducted by scientists. Experimental failures can result from farmer withdrawal, errors in treatment application or harvest, or non-provision of yield data by farmers. This paper describes the development and testing of approaches for on-farm experimentation and concludes which approaches should be adopted to maximise success. The programme of work included the largest on-farm research network in the UK, with farmers conducting around 50 on-farm experiments per year from 2017 to 2019 to compare fungicide programmes in winter wheat. The project developed management approaches to mitigate the risks of experimental failure such that in 2019, 96 % of experiments were completed and returned a yield result; a greater success rate than is commonly achieved in on-farm experiments. Statistical analysis of yield maps resulted in an average site SED (standard error of the difference between means) of 0.26 t/ha, which is comparable to that achieved in randomised, replicated small plot experiments. The large number of experimental sites enabled a greater level of precision in the cross-site analysis (SED 0.06 t/ha), showing the potential of on-farm experiments for detection of small yield effects if the appropriate yield analysis is undertaken. The project results received substantial publicity within the UK arable farming community, demonstrating the value of effective on-farm research for engaging and informing farmers. • On-farm experiments risk failure from treatment or harvesting errors, or non-provision of yield data by host farmers. • Risks can be mitigated by good farmer liaison, marking test tramlines, and providing instructions for yield data transfer. • Large series of on-farm experiments deliver precise comparisons of agronomic inputs in commercial situations. • The results of on-farm experiments are relevant and persuasive for the farming community.

Breeding and Agronomic Research on Lodging Resistance and Culm Strength of Japanese Wheat Cultivars

Breeding and Agronomic Research on Lodging Resistance and Culm Strength of Japanese Wheat Cultivars

Interpretable machine learning methods to explain on-farm yield variability of high productivity wheat in Northwest India

The increasing availability of complex, geo-referenced on-farm data demands analytical frameworks that can guide crop management recommendations. Recent developments in interpretable machine learning techniques offer opportunities to use these methods in agronomic studies. Our objectives were two-fold: (1) to assess the performance of different machine learning methods to explain on-farm wheat yield variability in the Northwestern Indo-Gangetic Plains of India, and (2) to identify the most important drivers and interactions explaining wheat yield variability. A suite of fine-tuned machine learning models (ridge and lasso regression, classification and regression trees, k-nearest neighbor, support vector machines, gradient boosting, extreme gradient boosting, and random forest) were statistically compared using the R 2 , root mean square error (RMSE), and mean absolute error (MAE). The best performing model was again fine-tuned using a grid search approach for the bias-variance trade-off. Three post-hoc model agnostic techniques were used to interpret the best performing model: variable importance (a variable was considered “important” if shuffling its values increased or decreased the model error considerably), interaction strength (based on Friedman’s H-statistic), and two-way interaction (i.e., how much of the total variability in wheat yield was explained by a particular two-way interaction). Model outputs were compared against empirical data to contextualize results and provide a blueprint for future analysis in other production systems. Tree-based and decision boundary-based methods outperformed regression-based methods in explaining wheat yield variability. Random forest was the best performing method in terms of goodness-of-fit and model precision and accuracy with RMSE, MAE, and R 2 ranging between 367 and 470 kg ha −1 , 276–345 kg ha −1 , and 0.44–0.63, respectively. Random forest was then used for selection of important variables and interactions. The most important management variables explaining wheat yield variability were nitrogen application rate and crop residue management, whereas the average of monthly cumulative solar radiation during February and March (coinciding with reproductive phase of wheat) was the most important biophysical variable. The effect size of these variables on wheat yield ranged between 227 kg ha −1 for nitrogen application rate to 372 kg ha −1 for cumulative solar radiation during February and March. The effect of important interactions on wheat yield was detected in the data namely the interaction between crop residue management and disease management and, nitrogen application rate and seeding rate. For instance, farmers’ fields with moderate disease incidence yielded 750 kg ha −1 less when crop residues were removed than when crop residues were retained. Similarly, wheat yield response to residue retention was higher under low seed and N application rates. As an inductive research approach, the appropriate application of interpretable machine learning methods can be used to extract agronomically actionable information from large-scale farmer field data. • Data-driven agronomic research requires new analytical and methodological approaches. • Machine learning methods were used to disentangle complex relationships in farmer field data. • Model-agnostic tools were used to derive agronomic interpretations. • Residue management and N application rate were important management variables for wheat yield. • Residue management interacted with other practices to explain wheat yield variability.

RECALCITRANCE POTENTIAL OF WHEAT HYBRIDS AND LOCAL CULTIVAR AGAINST YELLOW RUST DISEASE AND WEEDS DENSITY UNDER CLIMATIC CONDITION OF PESHAWAR, KHYBER PAKHTUNKHWA

Wheat cultivars can be severely affected by new race of leaf and stripe rust which possessing Yr27 resistance gene in Pakistan and worldwide during previous four years. Thus, great importance could be given to develop new wheat cultivar that could resist leaf and stripe rust diseases. Yellow rust disease is caused by certain pathogens like basidiomycete fungus Puccina striiformis Westend f. species tritici Eriks, it is one of the most devastating foliar diseases of wheat in Pakistan and worldwide. Two years experiments were conducted in Agronomy Research Farm, The University of Agriculture Peshawar, Pakistan to evaluate the potential response of wheat hybrid lines (18A-1 and 18A-2) in comparison with local check (Ghaneemat-2016) against yellow rust disease.Results exhibited that wheat hybrid 18A-1 depicted resistant (R) with coefficient of infection (CI) of 0.1. Hybrid wheat 18A-2 showed host reaction (10MR) with coefficient of infection (4.0). Contrary to this, local wheat variety (Ghaneemat-2016) showed moderate susceptibility (30MS) type of host reaction with 24 CI value during season 2018-19. A moderate resistant (MR) type of host reaction with CI (16.0) was observed for local variety (Ghaneemat-2016) during season 2019-20. Among wheat hybrids 18A-2 depicted no visible infection while 18A-1 exposed resistant 1R type of host reaction with CI (0.2) during 2019-20.Chinese wheat hybrids have the high potential to resist against yellow rust as compared with local check variety. Higher weeds density, fresh and dry weeds density increased by increasing irrigation frequencyfor local check Ghaneemat-2016 when sown early (15th November). Conclusively, from the study it is statedin wheat breeding program, identification of molecular markers facilitates the marker assisted selection of the resistance genes against yellow rust diseases, furthermore molecular markers should be used for marker assisted permitted that efficiently screening the large population.

Physico-Chemical Characterization of Soils for the Promotion of Precision Agriculture in Irrigated Rice Cultivation in the Zio Valley in Togo

To sustainably improve rice production in the Zio valley, this study characterized the soils of the developed area. More specifically, the study: (i) determined the Physico-chemical properties of soils and (ii) analyzed the impact of rice cultivation on these chemical parameters. Thirty-six (36) fields of producers were selected and distributed in the 4 villages of the irrigated perimeter: 10 in Kovié, 9 in Mission Tové; 9 in Ziwonou, and 8 in Assomé. The samples were manually collected at a depth of 0-30 cm and analyzed at the soil laboratory of the Togolese Institute of Agronomic Research (ITRA). Physically, the soils are sandy-loamy in Kovié (100%), sandy-loamy in Mission Tové (56%), clayey in Assomé (57%), and Ziovonou (78%). Chemically, the soils are acidic with an average pH of 5.57. They present low (0.89%) and moderate (1.3%) limitation levels respectively for nitrogen and organic matter, very severe for assimilable phosphate (2.3±0.16 ppm), and cation exchange capacity (4.64±0.26 meq/100g of soil) and severe for exchangeable potassium (0.14±0.01 meq/100g of soil). The study also showed a significant decrease in the quantities of Nitrogen, Carbon, Potassium exchangeable, and cation exchange capacity respectively of 57%, 72%, 56%, and 85% compared to 1964. The adoption of cultural practices having a less negative impact on the chemical characteristics of the soil combined with an update of the adapted fertilization formulas become imperatives to ensure sustainable exploitation of the perimeter.