Abu Zar Ghafoor

The aim of this study was to evaluate the effect of long-term crop rotation and fertilization treatments on the yield and yield component stability of spring barley and winter wheat on the basis of selected data over 30 years. The stability was measured using statistical methods (the Shukla stability index and linear mixed models). The long-term field experiments established in 1955 were conducted in central Poland (Chylice near Warsaw, 52°06′ N, 20°33′ E) and consisted of two crop rotations with the same fertilization regime. The first field experiment (A—NOR) is typical of the Norfolk rotation and consists of the following four crops: 1. sugar beet, 2. spring barley with undersown red clover, 3. red clover, and 4. winter wheat, while the second field experiment (B—NONleg) contains a sequence of crops without legumes: 1. sugar beet, 2. spring barley, 3. winter rapeseed, and 4. winter wheat. The following fertilization regimes are used in both experiments: a control without any fertilization (O), mineral fertilization (NPK), farmyard manure (FM), and mixed mineral and organic fertilization (½ NPK + ½ FM). The average yields of winter wheat and spring barley (in t*ha⁻¹) were 4.34 (a max of 5.48 in NONleg_NPK) and 4.27 (a max of 5.67 in NONleg_NPK) in the NONleg rotation treatment and 5.39 (a max of 6.12 in NOR_NPK) and 4.28 (a max of 5.22 in NOR_½ NPK + ½ FM), respectively, in the legume-based NOR rotation treatment. In the legume-free rotation treatment, the highest yield stability was found in the treatments fertilized only with manure (NONleg_FM) and in a mixed manner (NONleg_½NPK + ½FM), while in the Norfolk rotation treatment, the yield stability was the highest in the treatments with mixed fertilization (NOR_½NPK+½FM) and the treatments in which only mineral fertilizers were used (NOR_NPK).

Obtaining optimal wheat cultivars that balance high productivity and grain processing quality in diverse environmental and crop management conditions requires a comprehensive assessment of the influence of genetic and environmental factors and their interactions. This study investigated the influence of these factors on yield, grain quality, and bread-making traits in spring wheat (Triticum aestivum L.) cultivars. The study was conducted at four trial locations in the temperate climate area over two consecutive growing seasons, each with two different crop management approaches (moderate and high input). We observed a strong influence of genotype on grain quality (e.g., protein content, test weight) and farinographic in spring wheat. Environmental factors strongly influenced the variability of dough softening and quality number among the studied rheological traits. However, we observed that crop management significantly impacted dough stability. The strength of the relationships between yield, grain quality, and bread-making traits depended on the specific crop management used. The multi-trait stability of genotypes in yield, grain quality, and bread-making traits also varied, depending on the crop management method.

Biological nitrogen fixation (BNF) in legume crops is a crucial ecosystem service that enhances soil nitrogen and reduces the need for chemical fertilisers. This study evaluates the factors influencing the proportion of plant nitrogen derived from atmospheric fixation (Ndfa) in legume crops. We compiled a global dataset spanning from 1980 to 2018 and used the ¹⁵N method to assess the impacts of crop species, climatic conditions, stand composition and nitrogen fertilisation on Ndfa. The global meta‐analysis reveals that the percentage of nitrogen derived from atmospheric fixation (Ndfa) in legumes ranges from 5% to 99%, with an average of 68%. Fodder legumes exhibited higher Ndfa, averaging 75%, while grain legumes showed more variability, ranging from 38% to 85%, depending on species and climatic conditions. The significant variability in Ndfa underscores the complexity of the process, which is influenced by species‐specific traits, ecological conditions and competition in mixed stands. However, the current data is insufficient for precise Ndfa estimation in nitrogen balances and decision support tools. The study highlights the need for further research on the impact of nitrogen fertilisation and stand composition on Ndfa. These findings emphasise the potential of BNF to support sustainable agriculture by improving nitrogen availability and reducing dependence on synthetic fertilisers and particularly susceptibility to climate change challenges. To optimise the benefits of BNF, future research should focus on refining fertilisation regimes and exploring species‐specific responses to various ecological conditions. Exploring adaptive strategies, like selecting drought‐tolerant legumes and optimising irrigation, is essential. This will enhance the application of BNF in diverse agricultural systems, contributing to more sustainable and efficient farming practices.

In many parts of the world, solar radiation has decreased during the past 50 years due to industrialisation‐induced elevations in air aerosols which has negatively impacted crop productivity. Climate change threatens rapeseed (Brassica napus L.) production due to shade stress caused by reduced light radiation. However, studies on how shade affects photosynthetic mechanisms in rapeseed (leaves and pod wall) are not well documented. Understanding the mechanisms of shade on yield formation in rapeseed is important for breeding shade‐tolerant rapeseed varieties and optimising agricultural management practices in low‐light areas. Therefore, this study assesses the impacts of ‘global dimming’ simulated by shading at a specific period on rapeseed's photosynthetic behaviour, yield and seed quality. A two‐factor split‐plot design was arranged with three shading treatments (CK, FS and PS) and two hybrid genotypes (Chuannong and Zhongyouza) of rapeseed. We observed that shading at the flowering stage (FS) significantly inhibited the leaf area index, chlorophyll content, photosynthetic efficiency and enzymatic activities of both genotypes. Besides that, shading at pod development stage (PS) substantially declined the pod photosynthetic characteristics and transportation of carbohydrates towards economic organ (seeds) which directly decreased the yield of rapeseed. We found that PS treatment remarkably declined the oil content of both genotypes. According to the results, the photosynthetic capacity of rapeseed pod wall had a greater impact on yield and seed quality than leaves. Therefore, improving the photosynthetic capacity and material transport efficiency of the pod wall is a potential measure to increase the yield of rapeseed under shade stress. This study provides a new insight into the effects of shade on rapeseed production and provides a valuable reference for rapeseed breeding techniques to develop high‐yielding genotypes by enhancing the photosynthetic efficiency of rapeseed pod wall in low‐light conditions.

This comprehensive review examined the intricate relationship between climate change and rye (Secale cereale L.) production, focusing on the multifaceted challenges and opportunities posed by changing environmental conditions. Rye is a versatile cereal crop cultivated in temperate regions and is known for its resilience and adaptability to adverse growing conditions. However, as global temperatures and atmospheric CO₂ concentrations rise, the effects of climate change on rye growth, yield and grain quality become increasingly apparent. In this review, we summarised the recent research findings on various aspects of rye production and quality under climate change, focusing on factors such as temperature (e.g., increasing temperature) resilience, and viability of rye production in the face of ongoing climate challenges, altered rainfall patterns (changing rainfall distributions with decreasing rainfall in the spring and early summer months as well as heavy rainfall events), biotic stress, agronomic practices and greenhouse gas emissions. Exploring the dynamic interplay among climate change, soil quality, biotic stressors and plant–microbe interactions reveals insights into the response of rye to environmental changes. These interactions shape the complex dynamics that influence the adaptation of rye to evolving environmental conditions. Implications for food security, agricultural sustainability and future research directions are also discussed, highlighting the urgent need for adaptive strategies to ensure the resilience and viability of rye production in the face of ongoing climate challenges.

This study examines the significant variability in grain yield, thousand-grain weight, protein content, sedimentation value, and falling number among winter wheat cultivars across diverse trial locations, elucidating the profound influence of environmental factors on these traits. Employing Shukla’s stability variance and a multi-trait stability index (MTSI), cultivar stability is comprehensively assessed across multiple traits. Cultivars are ranked based on stability variance and cumulative ranking across all traits, with Bataja emerging as the most stable cultivar according to Shukla variance, while Apostel exhibits the lowest stability. Contrarily, MTSI rankings reveal distinct top performers, such as Medalistika and KWS Spencer. Canonical correspondence analysis (CCA) is utilized to discern relationships between stability and genotype characteristics, as well as trait values and soil properties/weather conditions. These findings contribute to the recommendation of stable cultivars for breeding programs and the optimization of crop management practices. Furthermore, this study underscores the need to explore causal relationships between accompanying variables, facilitating informed recommendations for plant breeders and advancing breeding progress amidst a changing climate. The use of multivariate statistical methods, including CCA, enhances our understanding of cultivar traits and stability, offering valuable insights for sustainable agriculture.

Leaf age is an important trait in the process of maize (Zea mays L.) growth. It is significant to estimate the seed activity and yield of maize by counting leaves. Detection and counting of the maize leaves in the field are very difficult due to the complexity of the field scenes and the cross-covering of adjacent seedling leaves. A method was proposed in this study for detecting and counting maize leaves based on deep learning with RGB images collected by unmanned aerial vehicles (UAVs). The Mask R-CNN was used to separate the complete maize seedlings from the complex background to reduce the impact of weeds on leaf counting. We proposed a new loss function SmoothLR for Mask R-CNN to improve the segmentation performance of the model. Then, YOLOv5 was used to detect and count the individual leaves of maize seedlings after segmentation. The 1005 field seedlings images were randomly divided into the training, validation, and test set with the ratio of 7:2:1. The results showed that the segmentation performance of Mask R-CNN with Resnet50 and SmoothLR was better than that with LI Loss. The average precision of the bounding box (Bbox) and mask (Mask) was 96.9% and 95.2%, respectively. The inference time of single image detection and segmentation was 0.05 s and 0.07 s, respectively. YOLOv5 performed better in leaf detection compared with Faster R-CNN and SSD. YOLOv5x with the largest parameter had the best detection performance. The detection precision of fully unfolded leaves and newly appeared leaves was 92.0% and 68.8%, and the recall rates were 84.4% and 50.0%, respectively. The average precision (AP) was 89.6% and 54.0%, respectively. The rates of counting accuracy for newly appeared leaves and fully unfolded leaves were 75.3% and 72.9%, respectively. The experimental results showed the possibility of current research on exploring leaf counting for field-grown crops based on UAV images.

A field experiment was conducted in 2018–2020 to investigate the effect of two nitrogen application rates (N₀ = 0 kg ha⁻¹(control), N₉₀ = 90 kg ha⁻¹, and N₁₈₀ = 180 kg ha⁻¹) on morphological and physiological behaviours of two new rapeseed varieties; V₁ = JYJS01 (semi-dwarf variety) and V₂ = CY36 (tall variety). Our results indicated that N application enhanced the plant growth and seed protein content in comparison to control. Contrastingly, compared with control, sugar contents, i.e. sucrose and reducing sugars, decreased significantly in response to an increase in N. Seed oil content also decreased by 8.5% and 5.5%, 6.7% and 3.9% against N₁₈₀ in V₁ and V₂ during 2019 and 2020, respectively. Furthermore, higher nitrogen application rates decreased seed fatty acid proportions by decreasing the sugar availability for fatty acid biosynthesis. Our results demonstrated the highest seed yield (9.4 g plant⁻¹ in 2018/19 and 9.5 g plant⁻¹ in 2019/20) in V₂ against N₁₈₀, and the lowest seed yield (3.2 g plant⁻¹ in 2018/19 and 3.4 g plant⁻¹ in 2019/20) in V₁ at control. These findings imply that a high nitrogen application rate had increased the yield. At the same time, the carbohydrates translocation from stems to seed for fatty acid biosynthesis decreased, which played their significant role in seed physiology for fatty acid metabolisms, ultimately affected the seed quality. However, there is still a dire need to evaluate how nitrogen application affect the carbohydrate availability for fatty acid metabolism in the seed of new winter rapeseed varieties. Graphical abstract

In the maize–soybean intercropping system, shade is the major chronic restraint that affects normal growth of soybean. Different spatial patterns of this system affect the microclimate of soybean through shading from maize plants. However, the negative impacts of shading stress can be mitigated by providing optimal ratios of different fertilizers. Therefore, to test this hypothesis, soybean plants were grown under different light conditions (normal light or shade) to evaluate the response to varying NH₄⁺/NO₃⁻ ratios. Seeds of soybean (Glycine max L. cv. Nan‐99‐6) were grown in nutrient solution with a total concentration of 5 mM N using different NH₄⁺/NO₃⁻ ratios (T₀ = 0:0, T₁ = 0:100, T₂ = 25:75, T₃ = 50:50 and T₄ = 75:25) for 40 days in a greenhouse at PPFD 320.95 μmol m⁻² s⁻¹ (low light) or 967.53 μmol m⁻² s⁻¹ (normal light). Under low light, growth and photosynthesis of soybean seedlings significantly decreased as compared to normal light conditions. However, the optimal ratios of NH₄⁺/ NO₃⁻ improved growth and photosynthesis of soybean seedlings under both light conditions. Our results indicated that soybean seedlings supplied with optimal NH₄⁺/NO₃⁻ ratios (25:75 and 50:50) have maximum biomass yield, chlorophyll pigments, leaf gas exchange, photochemical activity and root growth as compared to low and high NH₄⁺/NO₃⁻ ratios (T₁ and T₄). High ratios of NH₄⁺/NO₃⁻ (T₄) resulted in reduced plant growth due to nutrient accumulation in plant tissues; therefore, we suggest that optimal ratios of NH₄⁺/NO₃⁻ (T₂ and T₃) can enhance the shade tolerance of soybean seedlings.